THE UNIVERSITY OF HULL Factors affecting customer loyalty ...

THE UNIVERSITY OF HULL

Factors affecting customer loyalty of different strategic groups in the

Vietnamese supermarket sector

being a Thesis submitted for the Degree of Doctor of Philosophy

in the University of Hull

by

THI DIEM EM NGUYEN

BA, Business Administration, University of Economics Ho Chi Minh city (Vietnam), 2006

MSc, International Business and Management, University of East London (United Kingdom),

2012

January 2019

i

ABSTRACT

The main objective of this research is to investigate factors affecting customer loyalty of

different supermarket strategic groups, as the term of strategic groups in the grocery sector

appears to have been ignored by most researchers and the topic of comprehensive factors

affecting customer loyalty are is under-researched. There were two main phases of emperical

research, including expert and supermarket-consumer interviews (Phase One) and

questionnaire survey (Phase Two). In particular, there were 3055 questionnaires collected

from 17 March 2018 to 27 July 2018 in the Vietnamese supermarkets through many

channels, including email, postal and face-to-face contact. After data screening, 2913

questionnaires remained in the dataset. The three main quantitative techniques used were

exploratory factor analysis (EFA), confirmatory factor analysis (CFA) and structural equation

modelling (SEM). The research used both SPSS and AMOS 24. The results revealed there are

seven main direct indicators for customer loyalty: retail brand experience, service quality

related to in-store employees’ knowledge and attitudes toward consumers, customer

satisfaction, promotion effects, switching costs, e-service quality related to a core e-service

quality scale, and alternative attractiveness. In that, customer satisfaction can explain only

17.8 percent variation in customer loyalty. In addition, price, habit and income also have a

slight positive impact on customer loyalty. This research also revealed seven main factors

directly and positively affecting customer satisfaction: customer perceived value, in-store

logistics, service quality related to service employees’ knowledge and attitudes toward

consumers, store image, customer experience, product quality, and alternative attractiveness

negatively relating to customer satisfaction. Besides that, switching costs and price also have

a slight direct impact on customer satisfaction. Furthermore, this research also found factors

directly and positively affecting customer perceived value, including price, in-store logistics,

trust, promotion effects, e-service quality related to a core e-service quality scale, service

quality and customer service, and that switching costs are negatively associated with

customer perceived value. The research also investigated differences across groups, including

strategic groups, age ranges, location, gender, income, education level and occupation. The

results showed that there were differences between groups regarding factors affecting

customer loyalty, customer satisfaction and customer perceived value. It is believed that the

research will prove meaningful for both academia and practitioners in understanding issues

relating to factors affecting customer loyalty, especially since multigroup analysis was

conducted to examine different relationships between constructs in the researched model; the

research also revealed that the term ‘strategic groups’ in the grocery sector should not be

ignored. The revised research framework generated in this research can be applied in any

industry or market. There are some limitations to this research which are presented in section

8.3 and recommendations for future research.

ii

ACKNOWLEDGEMENT

My PhD has been one of the most incredible milestones in my life and especially my

academic career. Spending more than 2 years full-time research with ceaseless self-learning

motivation, I have become more knowledgeable which I hope will enable me to contribute

more to the quality of education in my country, Vietnam. This thesis would have been

impossible to complete without support and encouragement from my family, supervisors and

friends.

First of all, I would like to express my deepest gratitude to my family who have

always been there to support me during my research journey, especially my mother and father

who always encourage me and give me their unconditional love. In addition, two other people

that have always been there to encourage me are my cutest baby girl, Nguyen Xuan Huyen

Anh and my partner, Charles Buchanan-Price, without whom I might not have been able to

achieve the necessary application to complete my PhD journey. Again, thank you and I love

you all, my lovely family.

Secondly, I would like to express my grateful appreciation to my first supervisor,

Professor David Bruce Grant and my second supervisor, Professor Christopher Bovis of the

University of Hull who have always shown their support and dedication while advising and

guiding my PhD work. Their valuable direction from the start of my PhD facilitated and

enhanced my whole research journey. Thanks to my supervisors’ encouragement and

guidance, I undertook self-study on quantitative research which I consider a significant

achievement in my PhD journey, and the acquisition of knowledge has been beneficial and

supportive throughout my PhD work and will remain so for the remainder of my future

academic career. Besides that, any problems related to my academic work have been guided

and quickly solved by my two incredible supervisors. I learned many things from them, have

received valuable detailed feedback at our frequent meetings, and have continually been

made aware of the importance of the quality and consistency of my work. Without my

supervisors’ dedicated and patient support, I may not have been able to complete my PhD

work. Again, Professor Grant and Professor Bovis, I feel honoured to have been one of your

PhD students.

Thirdly, I would like to thank all of my friends, colleagues and previous students who

have supported me during the data collection process; without your support, I would not have

been able to collect sufficient data to support my work. Especially, I would like to express my

appreciation to Associate Professor Xuan Lan Pham, University of Economics Ho Chi Minh

City, who is an expert in strategy and retailing in Vietnam, whose comments on the

Vietnamese retailing strategic groups facilitated my research. Thanks for your networking

introductions which enabled me to connect with other experts and participants.

Last but not least, I would like to thank John Balcombe, retired Strategy Advisor to

the BBC Trust, who has supported me immensily with his unquestionably professional

proofreading.

iii

ABSTRACT ............................................................................................................................................ i

ACKNOWLEDGEMENT .................................................................................................................... ii

LIST OF FIGURES ........................................................................................................................... viii

LIST OF TABLES ................................................................................................................................ x

LIST OF APPENDICES .................................................................................................................... xii

LIST OF ABBREVIATIONS ........................................................................................................... xiii

Chapter 1: Introduction ....................................................................................................................... 1

1.1 INTRODUCTION .............................................................................................................................. 1

1.2. RESEARCH BACKGROUND ............................................................................................................ 1

1.3. CONTEXT OF STUDY ..................................................................................................................... 3

1.4. RESEARCH OBJECTIVES ................................................................................................................ 4

1.5. RESEARCH QUESTIONS ................................................................................................................. 4

1.6. RESEARCH METHODOLOGY .......................................................................................................... 5

1.7. POTENTIAL CONTRIBUTIONS OF THIS RESEARCH ......................................................................... 5

1.8. THESIS OUTLINE ........................................................................................................................... 6

Chapter 2: Literature review ............................................................................................................... 9

2.1. AN APPROACH USED FOR SEARCHING LITERATURE REVIEW ........................................................ 9

2.2. LITERATURE REVIEW- STRATEGIC GROUPS ............................................................................... 12

2.2.1. Introduction ......................................................................................................................... 12

2.2.2. Business strategy and its performance ................................................................................ 12

2.2.3. Strategic groups................................................................................................................... 15

2.2.3.1. The origins of strategic group theory ........................................................................... 15

2.2.3.2. Strategic group theory .................................................................................................. 18

2.2.4. Competitive positioning and competitive analysis ............................................................. 24

2.2.5. Summary ............................................................................................................................. 25

2.3. RETAIL INDUSTRY ...................................................................................................................... 26

2.3.1. Introduction ......................................................................................................................... 26

2.3.2. Retail ................................................................................................................................... 26

2.3.2.1. Definition of retail and brief report on current global retail industry .......................... 26

2.3.2.2. Trends in the retailing industry .................................................................................... 30

2.3.2.3. Types of Retailers ........................................................................................................ 32

2.3.2.4. Issues related to customer buying behavior ................................................................. 32

2.3.3. Summary ............................................................................................................................. 34

2.4. THE VIETNAMESE RETAIL INDUSTRY INSIGHTS ......................................................................... 34

2.4.1. Introduction ......................................................................................................................... 34

2.4.2. Overview about the Vietnamese retail industry .................................................................. 34

2.4.2.1. Traditional retail channels: Wet markets, “Mon and Pop” small independent grocery

stores ......................................................................................................................................... 41

2.4.2.2 E-commerce .................................................................................................................. 42

2.4.3. PESTEL analysis- Industry life cycle and the five forces model ........................................ 43

2.4.4. Drivers of change in the retail industry in Vietnam ............................................................ 52

2.4.4.1. The government’s control ............................................................................................ 52

2.4.4.2. Consumer behaviour patterns ....................................................................................... 52

2.4.4.3. E-commerce ................................................................................................................. 53

2.4.5. Summary ............................................................................................................................. 53

iv

2.5. CUSTOMER LOYALTY ................................................................................................................. 53

2.5.1. Introduction ......................................................................................................................... 53

2.5.2. Consumer tastes, consumer habits, consumer preferences and consumer behaviour ......... 54

2.5.3. Customer experience and customer perceived value .......................................................... 56

2.5.4. Consumer satisfaction ......................................................................................................... 64

2.5.5. Perceived switching barriers ............................................................................................... 68

2.5.6. Brand experience................................................................................................................. 73

2.5.7. Service quality .................................................................................................................... 76

2.5.8. Corporate factors ................................................................................................................. 81

2.5.8.1. In-store logistics and store image ................................................................................. 81

2.5.8.2. Store accessibility and loyalty ...................................................................................... 87

2.5.8.3. Customer service .......................................................................................................... 89

2.5.8.4. E-service quality .......................................................................................................... 92

2.5.8.5. Loyalty programmes and promotion effects ................................................................ 94

2.5.8.6. Product quality and price ............................................................................................. 96

2.5.9. Corporate social responsibility, corporate image and customer loyalty ............................. 97

2.5.10. Trust ................................................................................................................................ 100

2.5.11. Habit ................................................................................................................................ 100

2.5.12. Customer loyalty ............................................................................................................. 101

2.5.13. Research gaps, proposed research framework and hypotheses ....................................... 103

2.5.13.1. Research gaps ........................................................................................................... 103

2.5.13.2. The proposed conceptual research framework and hypotheses ............................... 105

2.5.14. Summary ......................................................................................................................... 109

Chapter 3: Research Methodology .................................................................................................. 111

3.1. INTRODUCTION ......................................................................................................................... 111

3.2. RESEARCH OBJECTIVES AND RESEARCH QUESTIONS RESTATED .............................................. 111

3.3. RESEARCH PHILOSOPHY AND RESEARCH PARADIGMS ............................................................. 112

3.3.1. Research philosophy and research paradigms ................................................................... 112

3.3.2. Apply paradigms to the thesis research ............................................................................. 116

3.4. ETHICAL THEORIES ................................................................................................................... 118

3.4.1. Philosophy and normative ethical theories ....................................................................... 118

3.4.2. Ethical paradigm and its implication................................................................................. 120

3.5. RESEARCH PROCESS ................................................................................................................. 121

3.6. THE CHOICE OF RESEARCH METHODOLOGY ............................................................................. 123

3.7. RESEARCH METHOD: PHASE ONE_ STEP ONE_EXPERT INTERVIEWING .................................. 126

3.7.1. Chosen research strategies: semi-structured interview ..................................................... 126

3.7.2. Sample and contacting the experts .................................................................................... 127

3.7.3. Interviewing guide development ....................................................................................... 129

3.7.3.1. Preparing an interview guide ..................................................................................... 130

3.7.3.2. Core questions ............................................................................................................ 132

3.7.3.3. Translation and back translation ................................................................................ 134

3.7.3.4. Conclusion ................................................................................................................. 136

3.7.4. Data collection .................................................................................................................. 136

3.7.5. Data analysis ..................................................................................................................... 137

3.8. RESEARCH METHOD: PHASE ONE _STEP TWO_SUPERMARKET CONSUMER INTERVIEWING ... 138

3.8.1. Sample size and contact .................................................................................................... 138

3.8.2. Interviewing contents ........................................................................................................ 139

v

3.8.3. Telephone and Internet-mediated interviews .................................................................... 139

3.8.4. Data analysis ..................................................................................................................... 140

3.9. RESEARCH METHOD: PHASE TWO_ QUESTIONNAIRE SURVEY................................................. 140

3.9.1. Survey Questionnaire ........................................................................................................ 140

3.9.2. Initial design and planning ................................................................................................ 141

3.9.2.1. Sampling frame identification .................................................................................... 142

3.9.2.2. Sample size ................................................................................................................ 142

3.9.2.3. Sampling design/sampling selection .......................................................................... 143

3.9.2.4. Locations selected for the study ................................................................................. 144

3.9.3. Scale Development, Reliability, Validity and replication ................................................. 144

3.9.3.1. Scale development ..................................................................................................... 145

3.9.3.2. Reliablility - Replication - Validity............................................................................ 146

3.9.4. Triangulation ..................................................................................................................... 150

3.9.5. Questionnaire Design and questionnaire construction ...................................................... 151

3.9.6. Data collection .................................................................................................................. 154

3.9.7. Data analysis ..................................................................................................................... 157

3.9.7.1. Exploratory factor analysis ........................................................................................ 158

3.9.7.2. Confirmatory factor analysis ...................................................................................... 159

3.9.7.3. Structural Equation Modeling_Goodness of fit ......................................................... 159

3.10. CONCLUSION .......................................................................................................................... 162

Chapter 4: Phase One - Qualitative data analysis.......................................................................... 164

4.1. STEP ONE - ANALYSIS FOR EXPERT INTERVIEWING: STRATEGIC GROUP MAPPING ................. 164

4.1.1. Introduction ....................................................................................................................... 164

4.1.3. Data analysis and discussion ............................................................................................. 165

4.1.4. Conclusion ........................................................................................................................ 170

4.1.5. Summary ........................................................................................................................... 170

4.2. STEP TWO - ANALYSIS FOR CONSUMER INTERVIEWING: CUSTOMER LOYALTY PERCEPTION .. 170

4.2.1. Introduction ....................................................................................................................... 170

4.2.3. Data analysis and discussion ............................................................................................. 173

4.2.4. Conclusion ........................................................................................................................ 190

Chapter 5: Phase Two - Quantitative data analysis ....................................................................... 193

Survey Descriptive Statistics and Exploratory Factor Analysis ................................................... 193

5.1. INTRODUCTION ......................................................................................................................... 193

5.2. DATA PREPARATION AND DATA SCREENING ............................................................................ 193

5.2.1. Data preparation ................................................................................................................ 193

5.2.2. Data screening ................................................................................................................... 193

5.2.2.1. Missing data ............................................................................................................... 193

5.2.2.2. Identification of outliers ............................................................................................. 194

5.2.2.3. Normality test - statistics ............................................................................................ 195

5.2.3. Response rate and Non-response bias ............................................................................... 196

5.3. DESCRIPTIVE STATISTICS ......................................................................................................... 197

5.3.1. Respondent demographic data .......................................................................................... 197

5.3.2. Shopping behaviour - Respondents’ choices .................................................................... 199

5.3.3. Mean and standard deviation values for all constructs ..................................................... 199

5.4. INTERNAL CONSISTENCY .......................................................................................................... 201

5.5. EXPLORATORY FACTOR ANALYSIS ........................................................................................... 203

5.5.1. The results from Exploratory factor analysis .................................................................... 203

vi

5.5.2. Conclusion ........................................................................................................................ 206

5.6. THE REVISED MODEL ................................................................................................................ 206

Chapter 6: Confirmatory factor analysis and structural equation modelling ............................ 208

(Construct validation and hypothesis testing) ................................................................................ 208

6.1. INTRODUCTION ......................................................................................................................... 208

6.2. UNIDIMENSIONALITY - INITIAL MODEL FIT .............................................................................. 208

6.3. CONSTRUCT VALIDITY ............................................................................................................. 211

6.3.1. Convergent and discriminant validity ............................................................................... 211

6.3.1.1. Convergent validity .................................................................................................... 211

6.3.1.2. Discriminant validity .................................................................................................. 211

6.3.1.3. Criteria summarizing.................................................................................................. 212

6.3.2. Results from construct validity ......................................................................................... 212

6.3.2.1. Convergent validity .................................................................................................... 212

6.3.2.2. Discriminant validity .................................................................................................. 216

6.3.2.3. Conclusion ................................................................................................................. 220

6.4. COMMON METHOD BIAS ........................................................................................................... 220

6.5. FINAL MEASUREMENT MODEL FIT ............................................................................................ 220

6.6. STRUCTURAL MODELS .............................................................................................................. 221

6.6.1. Multivariate assumptions .................................................................................................. 221

6.6.1.1. Outliers and influentials ............................................................................................. 221

6.6.1.2. Multicollinearity analysis ........................................................................................... 222

6.6.2. Structural model validity ................................................................................................... 224

6.6.3. Results from hypothesis testing ........................................................................................ 225

6.6.3.1. Direct effects .............................................................................................................. 225

6.6.3.4. Multigroup analysis.................................................................................................... 231

6.6.3.4.1. Comparison between retail strategic groups ....................................................... 231

6.6.3.4.2. Comparison between gender ............................................................................... 236

6.6.3.4.3. Comparison between income groups .................................................................. 237

6.6.3.4.4. Comparison between location ............................................................................. 240

6.6.3.4.5. Comparison between age groups ........................................................................ 242

6.6.3.4.6. Comparison between occupation ........................................................................ 246

6.6.3.4.7. Comparison between education levels ................................................................ 249

6.6.3.5. Conclusion ................................................................................................................. 251

Chapter 7: Discussion of the findings .............................................................................................. 252

7.1. INTRODUCTION ......................................................................................................................... 252

7.2. DIRECT EFFECTS’ DISCUSSION .................................................................................................. 252

7.2.1. Results from all hypotheses related to customer perceived value (CPV) ......................... 252

7.2.2. Results from all hypotheses related to customer satisfaction (CS) ................................... 257

7.2.3. Results from all hypotheses related to customer loyalty (CL) .......................................... 263

7.3. MULTI-GROUP COMPARISONS’ DISCUSSION (COMPARISONS ACROSS GROUPS FOR FACTORS

RELATED TO CUSTOMER LOYALTY) ................................................................................................ 272

Chapter 8: Conclusion ...................................................................................................................... 279

8.1. INTRODUCTION ......................................................................................................................... 279

8.2. SUMMARY OF MAIN FINDINGS .................................................................................................. 279

8.2.1. Conclusions regarding the research questions .................................................................. 279

8.2.2. Other conclusions .............................................................................................................. 284

vii

8.2.3. Contributions to theory, methodology and practice .......................................................... 285

8.2.3.1 Contribution to theory ................................................................................................. 285

8.2.3.2. Contribution to methodological level......................................................................... 286

8.2.3.3. Contribution to practice ............................................................................................. 288

8.3. THESIS LIMITATIONS AND RECOMMENDATIONS FOR FUTURE RESEARCH ............................... 290

REFERENCES .................................................................................................................................. 293

APPENDICES ................................................................................................................................... 329

viii

LIST OF FIGURES

Figure 1.1: A structure of thesis .............................................................................................................. 8

Figure 1.2: The process of selecting articles reviewed for this study ................................................... 11

Figure 2.2.1: The basic SCP model....................................................................................................... 18

Figure 2.2.2: Ilustrative map of the US chain saw industry .................................................................. 22

Figure 2.2.3: Average net profit before tax for market specialisation and company ownership .......... 22

Figure 2.2.4: Average net profit before tax for company’s pricing strategy and most important

customer type ........................................................................................................................................ 23

Figure 2.2.5: Strategic groups scheme .................................................................................................. 23

Figure 2.2.6: BCG matrix ..................................................................................................................... 25

Figure 2.2.7: Porter’s Five Forces Model – Fundamental determinants of industry competition ........ 25

Figure 2.3.1: Distribution Channel ....................................................................................................... 27

Figure 2.3.2: Top 250 quick statistics, FY2015 .................................................................................... 27

Figure 2.3.3: The top 20 global retailers, FY 2014 ............................................................................... 28

Figure 2.3.4: The top 20 global retailers, FY 2015 ............................................................................... 29

Figure 2.3.5: Global retail geographic analysis .................................................................................... 30

Figure 2.3.6: Stages in the Buying Process ........................................................................................... 33

Figure 2.4.1: The population pyramid of Vietnam ............................................................................... 35

Figure 2.4.2: Vietnam’s urban population ............................................................................................ 43

Figure 2.4.3: PESTLE analysis ............................................................................................................. 44

Figure 2.4.4: Vietnam inflation rate ...................................................................................................... 46

Figure 2.4.5: Vietnam GDP per capita .................................................................................................. 48

Figure 2.4.6: Industry life-cycle ............................................................................................................ 49

Figure 2.4.7: The Five Forces model .................................................................................................... 50

Figure 2.5.1: Factors affecting customer behaviour.............................................................................. 54

Figure 2.5.2: Application of the sequential incident technique to touch point research ....................... 58

Figure 2.5.3: Some ways in which customers measure their satisfaction ............................................. 66

Figure 2.5.4: Elements of customer service .......................................................................................... 66

Figure 2.5.5: The conceptual framework .............................................................................................. 71

Figure 2.5.6: Determinants of Perceived Service Quality..................................................................... 79

Figure 2.5.7: Service Quality Model ..................................................................................................... 79

Figure 2.5.8: Five dimensions of SERVQUAL model ......................................................................... 80

Figure 2.5.9: Entities in retail store operation ....................................................................................... 83

Figure 2.5.10: In-store logistics process ............................................................................................... 84

Figure 2.5.11: The relationship between in-store logistic, customer satisfaction and customer loyalty

.............................................................................................................................................................. 86

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Figure 2.5.12: The customer service factors ......................................................................................... 91

Figure 2.5.13: Historical development of service quality scale in online retail .................................... 93

Figure 2.5.14: The conceptual framework of e-service quality ............................................................ 93

Figure 2.5.15: Empirically validated model: coefficients ..................................................................... 94

Figure 2.5.16: General frustration model .............................................................................................. 96

Figure 2.5.17: Final causal relationships for virtual mobile service ..................................................... 98

Figure 2.5.18: Structural model estimation in the hotel sample ........................................................... 99

Figure 2.5.19: The proposed conceptual model of this research ......................................................... 107

Figure 3.1: Different logics used in quantitative and qualitative studies ............................................ 115

Figure 3.2: The research process......................................................................................................... 122

Figure 3.3: The research process onion .............................................................................................. 123

Figure 3.4: Steps in the process of conducting a mixed methods study.............................................. 124

Figure 3.P: Procedure of two phases conducted in this research ........................................................ 125

Figure 3.5: Formulating questions for an interview guide .................................................................. 130

Figure 3.6: Some main questions that should be covered in all qualitative interviews ..................... 132

Figure 3.7: Data collection processes in Phase One ........................................................................... 137

Figure 3.8: Planning a survey ............................................................................................................. 141

Figure 3.9: Stage in the development of the loyalty scale .................................................................. 145

Figure 3.10: Testing goodness of measures-forms of reliability and validity ..................................... 146

Figure 3.11: Data collection process applied in Phase Three ............................................................. 156

Figure 3.12: Types of questionnaire ................................................................................................... 157

Figure 3.R: Main results from two phases .......................................................................................... 163

Figure 4.1: Contents of Chapter 5 and Chapter 6................................................................................ 192

Figure 5.1: Normal Probability Plot .................................................................................................... 196

Figure 5.2: The revised model for main study .................................................................................... 207

Figure 6.1: Results from CFA_1strun .................................................................................................. 209

Figure 6.2: Results from outlier testing_Cook’s distance analysis ..................................................... 222

Figure 6.3: The second SEM (SEM_2nd

run) ....................................................................................... 225

Figure 6.4: The results of revised model of this research ................................................................... 230

x

LIST OF TABLES

Table LR (Literature review) 1-2: Literature review approach .............................................................. 9

Table 2.3.1: Types of Retailers ............................................................................................................. 32

Table 2.4.1: Main supermarkets in Vietnam ......................................................................................... 40

Table 2.4.2: Vietnam’s Grocery Retail Sales by Channel, trillion VND .............................................. 41

Table 2.5.1: Summary of experience antecedent researches ................................................................. 58

Table 2.5.2: Experience Measurement Method .................................................................................... 59

Table 2.5.3: Items for scale development ............................................................................................. 60

Table 2.5.4: Variables used for the retail brand experience (RBE) model ........................................... 76

Table 2.5.5: Differences between products and services ...................................................................... 78

Table 2.5.6: Retail site store location selection main criteria comparison martrix ............................... 88

Table 2.5.7: Comparison matrix of sub criteria for store location main criteria ................................... 88

Table 3.1: Comparison of positivism and interpretivism paradigms .................................................. 114

Table 3.2: Comparison of quantitative and qualitative methodologies ............................................... 115

Table 3.3: Distinction between Quantitative and Qualitative Data ..................................................... 117

Table 3.4: Comparisions between purposive and probability sampling techniques ........................... 128

Table 3.5: Advantages of non-probability sampling techniques ......................................................... 129

Table 3.6: Structural of semi-structured interview protocol in Phase One (Step One) ....................... 134

Table 3.7: Translation techniques for questionnaires ......................................................................... 135

Table 3.8: The process of data analysis .............................................................................................. 138

Table 3.9: Advantages of Probability Sampling Techniques .............................................................. 144

Table 4.1: Details of interviewees from Phase One (supermarket consumers) .................................. 172

Table 4.2: Interviewees’ descriptive information ............................................................................... 173

Table 5.2: The descriptive statistics for all items in the dataset .......................................................... 201

Table 5.3: All remained variables after EFA ...................................................................................... 205

Table 6.1: Model fit of CFA_1strun .................................................................................................... 210

Table 6.3: Results from CFA_2thrun_Discriminant validity checking ............................................... 216

Table 6.4: Results from CFA_2nd

run, the correlation between RBEX and other constructs .............. 217

Table 6.5: Model fit from CFA_3rd

run ............................................................................................... 217

Table 6.6: Results from CFA_3thrun_ Discriminant validity checking .............................................. 217

Table 6.7: Results from data analysis (CFA_3rd

run) .......................................................................... 218

Table 6.8: Model fit of CFA_4thrun .................................................................................................... 218

Table 6.9: Results from CFA_4thrun_ Discriminant validity checking .............................................. 219

Table 6.11: Summarising results of CFA model fit ............................................................................ 220

Table 6.12: Results from zero constraints test .................................................................................... 220

Table 6.13: Multicollinearity analysis ................................................................................................ 224

xi

Table 6.14: Summarising results from SEM running (SEM_1strun, SEM_2

ndrun) ............................ 226

Table 6.M.1: Multigroup analysis for COOP or BIGC ad LOTTE MART ........................................ 232

Table 6.M.2: Multigroup analysis for COOP or BIGC and VINMART ............................................ 234

Table 6.M.3: Multigroup analysis for Lotte Mart and Vinmart .......................................................... 235

Table 6.M.4: Multigroup analysis for COOP or BIGC and AEON .................................................... 236

Table 6.M.5: Multigroup analysis for gender ..................................................................................... 237

Table 6.M.6: Multigroup analysis for “under 5 million VND (GB£170)” and “from 5 to 10 million

VND (GB£170-340)” income groups ................................................................................................. 238

Table 6.M.7: Multigroup analysis for “under 5 million VND (GB£170)” and “from 10 to 20 million

VND (GB£340-680)” income groups ................................................................................................. 239

Table 6.M.8: Multigroup analysis for Ho Chi Minh and Hanoi ......................................................... 240

Table 6.M.9: Multigroup analysis for Ho Chi Minh and Da Nang ..................................................... 241

Table 6.M.10: Multigroup analysis for Can Tho and Binh Duong ..................................................... 242

Table 6.M.11: Multigroup analysis for “18-22 and 22-30” age groups .............................................. 243

Table 6.M.12: Multigroup analysis for “22-30 and above 55” age groups ......................................... 244



Table 6.M.15: Multigroup analysis for “housewife and office staffs” occupation groups ................. 247

Table 6.M.16: Multigroup analysis for “students and self employment” occupation groups ............. 248

Table 6.M.17: Multigroup analysis for “self employment and office staffs” occupation groups ....... 249

Table 6.M.18: Multigroup analysis for “A levels and college, university” groups ............................ 250

Table 6.M.19: Multigroup analysis for “GCSE’s and college, university” groups ............................ 250

Table 7.1: Factors directly affecting customer perceived value.......................................................... 253

Table 7.2: Factors directly affecting customer satisfaction ................................................................ 258

Table 7.3: Factors directly affecting customer loyalty ........................................................................ 264

xii

LIST OF APPENDICES

Appendix 2.1 - All hypotheses proposed in this research ................................................................... 329

Appendix 2.2 - Linkage between hypotheses and research questions ............................................... 331

Appendix 2.3 - Latent factors and manifest varibles used in this research ......................................... 332

Appendix 3.1 – Research Ethics approval letter ................................................................................. 334

Appendix 3.2 - Guide used for expert’s semi-structured interviews................................................... 335

Appendix 3.3 – Questionnaire used in supermarkets’ consumer interviewing ................................... 337

Appendix 3.4 – Questionnaire survey ................................................................................................. 340

Appendix 3.5 - Measurement variables used from Section 2 to Section 6 in the questionnaire (Phase

Two) and code book for other questions used in questionnaire .......................................................... 349

Appendix 4.1 – Some more direct quote of supermarket’s consumer interviewing in Phase One ..... 354

Appendix 5.1 – Results from Tests of normality ................................................................................ 365

Appendix 5.2 - Normal probability plots ............................................................................................ 368

Appendix 5.3 – Independent samples test (Non-bias response).......................................................... 370

Appendix 5.4- Full pie-charts summarises all respondents’ demographic information...................... 374

Appendix 5.5 – The shopping behaviours of Vietnamese supermarket consumers ............................ 375

Appendix 5.6 – Internal consistency of all researched constructed before EFA ................................ 378

Appendix 5.7- KMO and Barlett’s Test- Communalities (EFA) ........................................................ 384

Appendix 5.8 - Total Variance Explained (EFA) ............................................................................... 385

Appendix 5.9 - Pattern matrix (EFA) .................................................................................................. 387

Appendix 5.10 – All measurement variables remained after EFA ..................................................... 390

Appendix 6.1 - Results from CFA_2ndrun ........................................................................................ 393

Appendix 6.2- The final CFAmodel_Results from CFA_4thrun_after construct validity checking ... 394

Appendix 6.3- Common method bias testing ...................................................................................... 395

Appendix 6.4 - The initial SEM (SEM_1strun) and its results ........................................................... 396

Appendix 6.5 - SEM_2rdrun_Final .................................................................................................... 397

Appendix 6.6 - Summarising all hypothesis testing results ................................................................ 399

Appendix 7.1- Comparison across groups for factors related to customer loyalty ............................. 400

Appendix 7.2- Comparison across groups for factors related to customer satisfaction ...................... 401

Appendix 7.3- Comparison across groups for factors related to customer perceived value ............... 403

xiii

LIST OF ABBREVIATIONS

CPV Customer perceived value

CS Customer satisfaction

CL Customer loyalty

ISL In-store logistics

SQ Service quality

ESQ E-service quality

ESQX1 E-service quality related to a website quality scale

ESQX2 E-service quality related a core quality scale

PROQ Product quality

CUSER Customer service

CUEXP Customer experience

STIMA Store image

COIMA Corporate image

CSR Corporate social responsibility

STAC Store accessibility

ALA Alternative attractiveness

SWC Switching costs

LPRO Loyalty programs

PROE Promotion effect

EFA Exploratory factor analysis

CFA Confirmatory factor analysis

SEM Structural equation modelling

CR Composite reliability, construct reliability

AVE Average variance extracted

MSV Maximum shared variance

RBV Resource-based view

1

Chapter 1: Introduction

1.1 Introduction

This introductory chapter presents some general background to the research conducted

by the researcher before explaining the context in which the empirical work will be explored.

Then, research problems will be indicated, followed by the approach used to investigate the

topics and will conclude with the structure of this thesis and its conclusions.

1.2. Research background

There are continuously debated theories related to customer loyalty and how firms can

achieve sustainable development. These issues are apparently proved to have a strong impact

on firms’ survival associated with their profits. The initial idea for this research in my area of

expertise, with five years experience researching the strategic management angle in business,

parallel with the question of how to keep customers loyal to a business. For this reason, the

researcher was skeptical about the term of strategic-groups in marketing, particularly when

looking at the relationships between factors affecting customer loyalty, which had been

largely under-researched. For example, whether satisaction is a main indicator of customer

loyalty as well as whether differences between factors affecting customer loyalty in a specific

industry exist in regarding to income, gender, location, age group, occupation and education

levels. The following contents will pave the way for the whole research by demonstrating

some basic information related to this research project.

The trends of globalisation and integration have made the world come closer and

customers around the world tend to move to the same consumption style. However, in many

cases, there are still different consumer behaviours in specific industries. The meaningful

considered question by most researchers and business practitioners is which factors affect

customer loyalty (El-Andt and Eid, 2016; Perez and Bosque, 2015; Gurlek et al., 2017;

Chang and Yeh, 2017; Chen and Hu, 2013) in specific business sectors. Customer loyalty is

defined as “a deeply held commitment to re-buy, re-patronise a preferred product or service

consistently in the future, thereby causing repetitive same-brand or same brand-set

purchasing, despite situational influences and marketing efforts having the potential to cause

switching behaviour” (Oliver, 1997:392). Many firms compete fiercely to attract more

2

customers. Customer loyalty is an ultimate goal and dream of all retailers; it could help firms

increase from 25-85 percent profit (Reichheld et al., 1990). According to Mutum et al.,

(2014), Stan et al. (2013), Qui et al. (2015), customers tend to be loyal to firms that offer

superior value compared to their rivals, and these customers are willing to have an intensive

relationship with firms over time that can help firms save much money for their marketing

campaigns as they launch new products or offer new services.

Based on strategic theories used in specific industries, different strategic groups might

have different factors affecting customer loyalty. Leask and Parker (2006) define a strategic

group as a group of corporations that employ the same or similar strategies in a specific

industry. The term strategic group seeks to identify configurations based on observing

firms’ behaviour and then explain differential performance. Similar characteristics of such

group will likely relate to cost structure, formal organisation, control systems, management

rewards and punishment. Such groups are important for retail logistics and supply chain

management (SCM) as different strategic positions of grocery retailers will shape their retail

supply chains and replenishment and fulfillment activities. However, previous research has

appeared not to investigate factors affecting customer loyalty in different strategic groups,

rather it examined specific industries and extrapolated results to the whole industry. This

means that the differences between strategic groups in the same industry have been ignored.

In addition, the relationship between customer satisfaction and customer loyalty as well as

which factors may affect customer loyalty has been unceasingly debated between scholars.

Kursunluoglu (2014:538) found “customer service had effects on customer satisfaction” and

“customer service could explain 13.9 percent of total variance in customer satisfaction and

12.5 percent of total variance in customer loyalty”. Kumar et al. (2013:258) demonstrated

that although there is a positive relationship between customer satisfaction and customer

loyalty, the variance that could be explained by just a satisfaction is very small (around 8

percent). Therefore, they proposed scholars should investigate customer loyalty with many

other variables such as customer perceived value, switching barriers and relational variables

such as trust, commitment, relationship age, and loyalty programme membership. In

contrast, Lou and Bhattacharya (2006) and Oliver (1997), Kim et al. (2004), Shankar et al.

(2003), Chadha and Kapoor (2009) found that customer satisfaction is a major driver of

customer loyalty and it is well-known and confirmed by many other researchers. Besides

that, factors constitute customer perceived value and customer satisfaction have also been

debated among scholars. Most studies, which relate to customer loyalty in the retailing

3

industry, have separately explored customer loyalty and specific factors such as brand

image, social responsibility, and switching cost. There is no research examining many such

factors simultaneously affecting customer loyalty.

Vietnam’s retail market is characterised as being one of the most dynamic markets in the

region with high annual growth rates. Hanoi and Ho Chi Minh City have been ranked

amongst the top 10 Asian cities for retail expansion in 2014. With a population of more than

93 million people, about 70 percent of them aged from 16 to 64 which is a factor in the

potential growth of the retail industry; this figure is also known as the “Golden retail index”

(Oxford Business Group, 2017) and Vietnam was placed sixth in the 2017 Global Retail

Development Index (GRDI) (Vietnamnet, 2017). In addition, from 2015 to 2020, Vietnam’s

urban population is forecast to grow by 2.6%, one of the highest growth rates in the region

(Retail in Asia, 2016; Le, 2016). With the population’s high propensity to absorb new things

and readily change consumption habits, the Vietnamese retail market can promise a huge

potential for both domestic as well as foreign investors. However, to the best of my

knowledge, there is no comprehensive published paper investigating customer loyalty in the

supermarket sector in Vietnam as well as Vietnamese consumption style. Therefore, in this

research, factors affecting customer loyalty of different strategic groups in the Vietnamese

food and consumer-goods industry will be explored. The findings will be of potential benefit

to all business and academic researchers, and strategic decision makers when they look at

customer loyalty of a specific industry in Vietnam, especially in applied business strategies

for sustainable success.

1.3. Context of study

Therefore, the aim of this thesis is to investigate factors affecting customer loyalty of

different strategic groups in Vietnamese supermarkets, as the term strategic groups in the

grocery sector has been ignored by most researchers and the topic of comprehensive factors

affecting customer loyalty is under-researched. The Vietnamese supermarkets have been

selected for four main reasons. Firstly, Vietnam’s retail industry is one of the most dynamic

markets in the region with high annual growth rates; there is a huge potential platform with

“Golden retail index” and profits as well as market share that investors can invest their

money to (Oxford Business Group, 2017). Secondly, supermarkets in Vietnam have been

generating a large amount of revenue compared to other modern retail formats (Vo, 2017).

Thirdly, it might be interesting to investigate customer loyalty in the Vietnamese retail

4

market due to a huge different culture across the country which could generate informative

findings. Finally, scholars understand the Vietnamese retail market via news posted in social

media and online newspapers in Vietnam, there are a limited number of official papers

published about the Vietnamese retail industry. Via this research, scholars and practitioners

can fully understand the whole picture of the Vietnamese retail industry, which will be

presented in Chapter 2.

1.4. Research objectives

Based on the background information the research objectives are as follows:

Provide insights into the Vietnamese retailing industry; classify all current

supermarket firms in Vietnam to their proper strategic groups.

Investigate factors directly affecting customer loyalty, customer satisfaction and

customer perceived value in Vietnamese supermarkets by simultaneously researching

and comparing different strategic groups.

Examine whether there are differences between factors affecting customer loyalty

based on age groups, location, income, gender, occupation and education level.

1.5. Research questions

There are five research questions proposed in this study based on the foregoing

background and research objectives:

RQ1: What factors directly affect customer loyalty in the Vietnamese supermarket sector and

at which level?

RQ2: Is customer satisfaction a major indicator for customer loyalty or not?

RQ3: What factors directly affect customer perceived value, customer satisfaction in the

Vietnamese supermarket sector and at what level?

RQ4: Are there any differences in terms of factors affect customer loyalty between strategic

groups in the Vietnamese retail industry?

RQ5: Are there differences between the factors affecting customer loyalty in the retail

industry based on income, gender, location, age groups, occupation and education levels?

5

1.6. Research methodology

Based on research objectives and research questions presented above, both primary data

and secondary data should be collected in order to answer the questions of which factors

affect customer loyalty and at what level. Therefore, this research is going to use a mixed

method involving both qualitative and quantitative research. Full explanation as to why this

methology should be used in this research will be presented in Chapter 3. The main

ontological and epistemological stances in this research are objectivism and positivism

respectively. The empirical study follows Cannon (2004) who suggested steps in the process

of conducting a mixed method which is believed to be the best way to investigate the gaps

presented later and answer all research questions, and it is comprised of two phases: Phase

One (Step One) is a strategic group mapping that all current supermarkets in Vietnam will be

grouped into different strategic groups based on interviewing experts in the Vietnamese retail

industry. Phase One (Step Two) is an inductive phase that will involve conducting semi-

structured interviews with about 21 consumers who currently shop at supermarkets across the

country, five main markets investigated will be Ho Chi Minh, Hanoi, Can Tho, Da Nang and

Binh Duong. Lastly, Phase Two will be a deductive phase that will consist of an edited

questionnaire survey related to factors affecting customer loyalty in Vietnam to test and

validate the variables and constructs which would be built based on background literature, the

conceptual model proposed in 2.5.13.2 and the results from Phase One (Step Two). In Phase

Two, descriptive statistics, including data frequencies, means, standard deviations and cross-

tabulation will be demonstrated. Exploratory factor analysis (EFA) will be used to examine

the data sets from the questionnaire and explore any latent constructs, remove duplicated

variables, determine underlying dimensions or factors which are not known a priori in a set of

correlated variables (Hair et at., 2011). Confirmatory factor analysis (CFA) and structural

equation modelling (SEM) will be used in this research to determine the validity, reliability

and relationships between many remaining variables after EFA. An analysis of SEM will also

be used in this research in order to demonstrate the relationships between constructs (Hair et

at., 2011).

1.7. Potential contributions of this research

Firsly, this research is going to generate a comprehensive research framework of factors

influencing customer loyalty, customer satisfaction and customer perceived value which can

be used by other researchers in the future to investigate other markets and industries. Based

6

on would-be-collected data in the Vietnamese grocery sector, the researcher will confirm the

relationship between constructs involved, which are benificial for practitioners, as well as

answer the question of whether satisfaction is a main indicator of customer loyalty. In

addition, the researcher expects to prove that the term strategic groups in any industry should

not be ignored when conducting multigroup analysis. The next potential contributions would

be mediation and moderation effects if possible. Finally, differences between the factors

affecting customer loyalty in the retail industry based on income, gender, location, age

groups, occupation and education levels will be revealed.

1.8. Thesis outline

The thesis is divided into 8 chapters. After this introductory chapter, the contents are as

follow:

Chapter 2: The objective of this chapter is presenting literature related to a research topic.

Section 2.1 will indicate the approach used for searching literature review.

Section 2.2 named “Literature review - strategic groups” has three main parts.

First, it provides knowledge around strategic groups, including emphasising the

importance of business strategy, review about some origins of strategic group

theories (resource based view and industrial theory), brief insight about strategic

group theory as well as how to shape firms into their specific groups. Then,

some literature related to competitive positioning and analysis will also be

mentioned. This section aims to demonstrate the meaning of strategic groups.

Then, Section 2.3 named “Retail industry”, will present a brief report on current

global retail industry, followed by trends in the retailing industry, which are

growing diversity of retail formats and globalisation, social media-driven

economy, changes in customers’ preferences. Then, the section will summarise

types of retailers and indicate many issues related to customer buying

behaviour.

Section 2.4 named “The Vietnamese retail industry – insights”, will demonstrate

the Vietnamese retail industry insight. In that, it focuses on the supermarket

format for food and consumer goods as well as current traditional retail channels

in Vietnam (wet or flea market, “Mom and Pop” small independent grocery

stores). Firstly, an overview of the Vietnamese retail industry, customer

7

preference will be explored, followed by PESTLE analysis, industry life cycle

and the five forces model applied in the Vietnamese retail industry. Finally,

drivers of change in the Vietnamese retail industry, which include the impact of

government control, consumer behaviour patterns, and e-commerce will be

presented.

Finally, Section 2.5 named “Literature review - Customer loyalty”, provides a

review of many aspects of customer loyalty such as customer taste and

preferences, customer experience and customer perceived value, customer

satisfaction, perceived switching cost and switching barriers, brand experience,

service quality and further dimensions related to corporate factors such as in-

store logistics and store image, store accessibility and store loyalty, customer

service, e-service quality and product quality. Finally, the debate around factors

affecting customer loyalty will be discussed and the research framework and

hypotheses will be proposed.

Chapter 3 : This chapter defines the research approaches and methodologies undertaken in

this thesis; it also indicates some issues relating to research quality, data

collection and analysis methods used during research (there are two phases of

empirical research conducted in this area).

Chapter 4: This chapter provides qualitative data analysis (results from Phase One - Step

One and Step Two).

Chapter 5: This chapter refers to the main study of this research, named “Survey descriptive

statistics and exploratory factor analysis” (Phase Two - Questionnaire survey).

Chapter 6: This chapter presents results from confirmatory factor analysis and structural

equation modelling (Phase Two - Questionnaire survey).

Chapter 7: This chapter aims to provide the interpretation of the findings and discussion.

Chapter 8: Conclusion of the research and the many implications that can be made. The

limitations of this research are also presented, followed by suggestions for future

research around the investigated topic.

Figure 1 will present the above information in a chart form:

8

Chapter 1: Introduction

Chapter 5: Phase Two – Survey

Descriptive Statistics and

Exploratory Factor Analysis

Chapter 6: Confirmatory factor

analysis and structural equation

modelling (Construct validation and

hypothesis testing)

Chapter 7: Discussion the findings

Chapter 2: Literature review

Chapter 3: Research methodology

Chapter 4: Qualitative data analysis

(Phase One)

Chapter 8: Conclusion

Figure 1.1: A structure of thesis

Based on these foundations, the next chapter will explore literature related to the research

topic.

9

Chapter 2: Literature review

2.1. An approach used for searching literature review

This aim of this section is to present an approach used for exploring the literature review.

Literature review plays a vital role in the development of any research area. It summarises

and establishes connections between previous works, demonstrates different streams and

results which can help researchers identify research gaps and provides opportunities for

proposing research directions (Martins and Pato, 2019). According to Webster and Watson

(2002:xv-xvi), “a high quality review is complete and focuses on concepts. A complete

review covers relevent literature on the topic and is not confined to one research

methodology, one set of journals, or one geographic region). Therefore, they suggested a

structured approach to determine source materials for literature review, including three main

steps: step one “the major contributions are likely to be in the leading journals”, focusing on

well-established journals of specific areas can be considered; step two of the process is “go

backward” by review citations for the articles identified in step 1 to decide which prior

articles should be examined; step three is “go forward” by using online database for that

specific field to identify articles citing the key articles identified in the previous steps, highly

related papers should be included in the review. Also, Webster and Watson (2002) also

suggested how to structure the review and they introduced both a concept-centric approach

and an author-centric approach which can be brieftly presented as follows:

Table LR (Literature review) 1-2: Literature review approach

Adapted from Salipante et al. (1982)

10

The above process can synthesise all highly-related papers which will be used to review.

As mentioned previously, the main objective of this research is to investigate factors affecting

customer loyalty of different strategic groups in the Vietnamese supermarket sector.

Therefore, it will relate to four themes/concepts: Strategic Groups, Retail Industry, the

Vietnamese Retail Context and Customer Loyalty. While exploring the literature reviewing

process, the research is going to focus on these themes in Chapter 2.

In order to engage deeply with the literature, all reading materials being used in this

research will be from online databases and books offered by University of Hull. In that,

reading some major books related to the retailing industry such as Levy and Weitz (2004),

Dawson and Lee (2004), Dawson et al. (2008) will enable the researcher to develop an

insight into the retailing industry, although it should be noted that the books noted above

were written by the UK’s retailing experts. In addition, following and adapting the guidance

of Webster and Watson (2002) on how to write a literature review, online database is now the

main resource for literature exploring. In these online databases, there are a huge number of

journals offered. The basic technique for searching is using key words relating to the four

themes mentioned above and some further key words attaching to those themes. Firstly, the

researcher is going to search the main keyword, and read many papers around that topic. And

then, if that reading highlights some new themes, the researcher will use the newly

highlighted keywords to explore the theme in greater depth. From the outset, the four main

themes mentioned above, revealed 2567 papers from 2007 to present. After eliminating

duplication, and loosely-related papers (2279), and based on specific research objectives and

concentrating on abstracts of papers found, there remained 288 papers which were used for

this thesis. The above filtering process was applied thoroughly for searching each core theme.

In references, the majority of listed papers were used for sourcing literature reviewed in this

thesis and articles selected for reviewing in this study should have been published in well-

established journals. For example, in order to explore the theories relating to strategic groups,

the researcher is going to employ an advanced search for “STRATEGIC GROUPS” with

updated papers (ie. an ideal paper can be after 2007), and then discover new keywords such

as “the origins of strategic groups” or “business strategy”. In respect of customer loyalty, the

keywords “CUSTOMER LOYALTY” will be searched first, only to discover a number of

new keywords based on this theme, such as “customer satisfaction”, “customer perceived

value”, “service quality”, “in-store logistics”, “customer behaviour” and so forth. This

technique will be applied to all four key themes. However, there are not many official

11

published reviews about the Vietnamese retailing industry on the two databases above, the

researcher will search the keywords “THE VIETNAMESE RETAIL INDUSTRY” via

Google and select high quality and reliable online magazines or news items to review in

respect of this theme. The above process explains how the literature review should be

structured and created. It guarantees that the following review (Chapter 2) matches with the

research’s objectives. The following figure (Figure 1.2) will briefly illustrate the process by

which the papers were filtered for this study:

Figure 1.2: The process of selecting articles reviewed for this study

Outline of literature review

In Chapter 2, the researcher is going to review all literature around the research topic

based on the themes indicated above. First, literature surrounding strategic groups will be

investigated (Section 2.2), followed by a review of the retailing industry (Section 2.3). Then,

Section 2.4 is going to demonstrate insights into the Vietnamese retail industry. Finally, many

factors related to customer loyalty will be presented (Section 2.5). The links between these

four themes can be explained as follows. Section 2.2: “Strategic groups” will investigate

theories related to strategic groups, the definition of strategic groups and why this term

should be considered; via the review, the potential outcome will help readers understand

clearly that researching customer loyalty in a retail industry should be linked with “strategic

groups” because each group of firms might have different factors affecting customer loyalty.

Section 2.3: “The retailing industry” will demonstrate and draw a clear picture of the current

12

situation of the global retailing industry, which is beneficial to give insight into the industry.

Then, Section 2.4: “the Vietnamese retail industry” will also shed light on the Vietnamese

current retail situation and its competitive environment, as well as drivers of change in this

industry in the Vietnamese market. Finally, in section 2.5: “Customer loyalty”, will review

all possible factors that might affect customer loyalty which can lead to research gaps,

research questions and hypotheses for this research and constitute to propose the conceptual

research framework of this thesis.

2.2. Literature review- Strategic groups

2.2.1. Introduction

As mentioned in the research objectives, this research will explore factors affecting

customer loyalty of different strategic groups in the Vietnamese supermarket sector.

Therefore, it will be evident that literature around strategic groups should be investigated. In

this part, the researcher sheds light on the linkage between business strategy and firms’

performance, followed by theories relating to strategic groups, including its origins and

strategic group mapping; finally, competitive positioning and competitive analysis are also

examined.

2.2.2. Business strategy and its performance

With the continued changing business environment, those who intend to survive in a

market place will need to consider their business strategies and make them fit with the

existing environment. Business strategy has generated a significant interest amongst scholars

and practitioners (Bapat and Mazumdar, 2015). The concept of strategy was articulated as the

so-called “mean” to help firms reach their business goals and the vital objective of business

strategy is to improve and increase firms’ performance by matching firms’ internal

competencies and values to its external environment (Porter, 1983; Zott and Amit, 2008). It

can help firms shape themselves into different business strategy groups in specific industries.

Varadarajan et al. (2011) and Gupta (2012: 170) stated “business strategy specifies how

business will compete in the marketplace”. Allen (2007) found that lacking strategic focus is

the main reason which has led many Japanese firms to fail; he also demonstrated how firms

such as Honda, Sony and Nintendo have succeeded in their businesses and how they “rise to

global dominance by their well-developed and defined corporate strategies”.

13

Fierce competition motivates firms to seek specific ways to compete with rivals and use

their own competitive advantages to consciously shape and proactively formulate their future

goals before conducting any business action (Bhimani and Langfield-Smith, 2007). Many

previous studies indicate the positive linkage between firms’ business strategy and firms’

performance (Kim et al., 2004; Parnel, 2010; Dess and Davis, 1984). There are a number of

approaches investigating strategy typologies and it has been proposed as follows: Utterback

and Abernathy (1975) proposed three approaches which are sales maximising, cost

maximising and performance maximising; Abell (1980) introduced the concepts of

differentiation and focus/niche orientation. Venkatraman (1989), Veett et al. (2009) also

identified three viable approaches, including “building, holding and harvesting”. Miles and

Snow (1978; 1986) identified four different strategic approaches which are analysers,

defenders, reactors and prospectors. Porter (1980) stated that organisations can apply low-

cost strategy, differentiation strategy, and focus or combination strategy based on their own

competitive advantages and their resources. These typologies have received much attention

and have become the most cited and tested, and most criticised by other scholars (Veett et al.,

2009). Cost leadership refers to producing low-cost products, which are supposed to provide

low-prices as a result, to make price-sensitive customers satisfied. This group can be divided

into two sub groups: type 1 which implies to offer products and service at the lowest price in

the market; and type 2 referred to as “low-cost best value” that offer customers the best price

value in the market. In this case, firms might discontinue any activities where they do not

enjoy cost advantages and could outsource these activities to firms possessing cost

advantages. Cost leadership can be achieved via mass production, economies of scale, access

to raw materials, mass distribution, or effective input cost (Allen et al., 2007). Type 2 of the

main strategies mentioned by Porter (1980) is referred to as “differentiation” which offers

exceptional characteristics and unique products and services to relatively price-insensitive

customers who are willing to pay a premium price. These unique characteristics are product

quality, after-sales support or high perceived value based on brand name. In addition, “focus

strategy” was introduced later by Porter, which serves the needs of a niche market, namely

“low-cost focus” and “best value focus”. These strategic-frameworks have been highly used

by scholars and practitioners. Helms et al. (1992), Wright et al. (1990) found that businesses

with a low-cost strategy might perform well because their low-cost position allows them to

attract more customers from other firms by offering products with low prices as a result.

Wortzel (1987) and Varadarajan (1985) stated that with a mature business environment (the

mature phase in an industry’s life cycle), firms tend to apply differentiation strategy to

14

achieve competitive advantages, whereas the low-cost strategy is thought to have no material

effect on businesses.

Porter (1996) stated that firms should choose only one of these strategies; if they confuse

or target their strategies somewhere in the middle, they might get stuck due to the inherent

differentiation between strategies (Acquaah and Yasai-Ardekani, 2008). However, there are

groups of researchers who encourage firms to use the combination strategy (differentiation

and cost leadership), since they proved that combination strategy is more effective (Kim et

al., 2004; Baroto et al., 2012, Miller and Dess, 1993; Walker and Ruekert, 1987). Some

organisasions such as Tesco, Toyota, IKEA have applied it successfully by offering low-cost

products and products with unique and competitive features simultaneously. These strategies

have created an unrivaled performance, which is beneficial to firms to some extent

(Soltanizadesh et al, 2016). It is clear that there are a number of factors influencing firms’

performance, including strategic behavioural emphasis, structural characteristics and business

strategy (Olson et al., 2005). Firms can shape their business strategies based on competitor

orientation, customer orientation, internal/cost orientation and innovation orientation (Bendle

and Vandenbosch, 2014; Montgomery et al., 2005; Kumar et al., 2011; Pleshko et al., 2014;

Kurmet and Vadi, 2013). For example, firms with competitor orientation might focus on how

to beat their rivals in a specific time, rather than finding the way to maximise their profits

(Bendle and Vandenbosch, 2014).

There are a limited number of studies about strategy in retailing (Dawson and Sparks,

1982; Fernie et al., 2010; Fernie and Spark, 2004; Levy and Weitz, 2004). Researchers tried

to form retail firms’ strategic types and explored the linkage between strategic choice and

firms’ performance (McGree and Petersen, 2000; Conant et al., 1993). Based on the strategic

options of Porter (1980), some scholars have also considered a business strategy in retail

markets in terms of low cost, differentiation and focus strategies (Helms et al., 1992; Dwyer

and Oh, 1988). The options chosen depended on price leadership orientation, merchandise

differentiation (Parks and Mason, 1990) or product market approach (Ansoff, 1957) such as

productivity improvement, penetration, market development and diversification. Hawes and

Crittenden (1984) investigated strategy in retail industry at a functional level, and found the

different performance between different strategic groups which were formed by firms’ scope

and resource allocation (Flavan and Polo, 1999; Carrol et al., 1992). For small retailers,

strategies might only be based on product specialisation or customisation and customer

15

service perspectives (Covin and Covin, 1990) and firms can differentiate themselves from

others via functional levels of strategies.

2.2.3. Strategic groups

2.2.3.1. The origins of strategic group theory

Resource-based view (RBV) theory

The resource-based view argues that firms with differences in resources and capabilities

are a foundation of different firms’ performance (Reger and Huff, 1993; Rouse and

Daellenbach, 1999; Goh et al., 2007; Solesvik and Westhead, 2010, Barney, 2001;

McNamara et al., 2003). In other words, the key difference amongst firms is their resources

and how they are used, deployed, or allocated by firms (Short et al., 2003). In the early

nineteenth century, Ricardo (1817) indicated that certain plots of land possessing natural

resources or similar advantages enabled their owners to earn more money via renting the

land, thanks to the increasing growth of surrounding cities and industrialised areas, with the

resultant scarcity of free land. The resource-based view is a major grounded theory in

strategic management (Liang et al., 2010). The first notion of a resource-based view had been

mentioned by Penrose (1959:7) who proposed that an organisation should be viewed as “a

collection of human and physical resources bound together in an administrative framework,

the boundaries of which are determined by the area of administrative coordination and

authoritative communication”. Then, Wernerfelt (1984) published an influential article which

explored firms’ resources and investigated how they affected firm outcomes. While these

foundation notions helped many researchers understand, the process still remained unclear.

Barney (1991) articulated these ideas in a comprehensive way in terms of looking at the

linkage between firms’ resources and sustainable competitive advantages. He indicated all

assets firms’ attributed could lead them to be more effective and efficient in their businesses.

Different classification of resources has been raised in the literature (Grant, 1991; Barney,

1991; Amit and Schoemaker, 1993; Bogaert et al., 1994). These resources were divided into

three groups including human capital, physical capital and organisational capital (Barney,

1991). Foss (1996) proposed two groups which are property-based and knowledge-based

resources. Olavarrieta and Ellinger (1997) combined these classifications and proposed three

categories including input factors (logistics-related input factors such as raw factors and raw

skills) which can be applied or transformed into firms’ assets. For example, good inventory

16

systems, efficient picking and loading skills, using effective computer-operating skills can

lead to firms’ higher performance. The second group is assets such as patents, brand names,

and all visible resources. The third group is capabilities. They also differentiated assets and

capabilities, with capabilities relating to the action of ‘doing’ while assets are associated with

the act of ‘having”. However, Somsuk et al. (2012) classified resources into four categories:

human, technological, financial and organisational. These can be tangible or intangible assets

(Barney, 1991, 2007) that can provide sustainable competitive advantages for firms if those

resources have VRIN characteristics (Valuable, Rare, Imperfectly imitable and Non-

substitutable). It is clear that other firms can hold and imitate tangible resources and deploy

these resources as implementing their businesses, but capabilities or the so-called knowledge-

based resources (intangible assets) cannot be easy to capture. These things can make the

differences between firms (Brush et al., 2001; Ray et al., 2004; Currie, 2003; Teece, 1998).

“The more a capability is utilised, the more it can be refined and the more sophisticated and

difficult to imitate it becomes” (Olavarrieta and Ellinger, 1997: 563). Barney (1991: 102) also

indicated situations when a firm can enjoy a sustainable competitive advantage “when it is

implementing a ‘value creating strategy’ not simultaneously being implemented by any

current or potential competitors and when these other firms are unable to duplicate the

benefits of this strategy”. In other words, a competitive advantage can be sustained as there is

no floor for other organisations to imitate or duplicate all successful strategies generated by

the firm. However, Smith et al. (1996) indicated some problematic aspects of the above

statement. Firstly, it is impossible to realise that current and potential rivals have ceased to

strive to duplicate one’s competitive advantage or will not seek a way to do so in the future.

Secondly, Barney (1991) did mention about RBV with focusing mostly on the outcomes and

avoiding mention of the process of building competitive advantages which can be created via

organisational learning.

Under the resource-based view, firms with valuable resource might obtain more

competitive advantages, but the criteria for “valuable aspects” is still unclear and depend on

specific cases (Priem and Butler, 2001). Traditional strategy models, such as Michael Porter’s

five forces model, have focused on analysing the company’s external competitive

environment and did not investigate inside the firm. In contrast, the RBV theory highlights

the importance of matching and fitting the firms’ internal capabilities and the external market

context in which the firm operates. Most researchers have confirmed that it is critical to

determine a strategic action based on individual firms’ resources and capabilities; and the

17

strategies used should allow each company simultaneously to best deploy its core

competencies and fit with the external environment.

Industrial organisation theory

“The theory of industrial organisation (IO) has by and large viewed the industry as a

homogeneous unit. Firms in an industry are assumed to be alike in all economically important

dimensions except for their size” (Porter, 1979:214). It aims to explain the differences in

performance amongst firms (Foss, 1996; Scherer and Ross, 1990; Michael, 2003). The

essence of IO had been developed by Chamberlin (1933), Sweezy (1939), Mason (1949),

Bain (1956, 1968), Caves and Porter (1977) and their followers. They stated that firms’

performance critically depends on the characteristics of the industrial environment where

firms compete with others. In IO theory, the structure-conduct-performance (SCP)

framework, which is also known as the Bain/Mason paradigm (Figure 2.2.1) investigates how

the structure of an industry (all factors which generate market competitiveness) influence the

conduct (the behaviours and strategies used) and firms’ performance (Lipczynski and Wilson,

2004). In that, firm conduct dimension relates to how firms compete in the market place, their

own strategies performance or firms’ choices in relation to price, quality, the level of

expansion, and advertising; performance was evaluated based on many factors which are

“allocative efficiency (profitability), technical efficiency (cost minimization), innovativeness

and others” (Porter, 1983:176). There are two perspectives being considered in SCP trilogy;

Bain (1956; 1968) stated that a structure has a significant effect on firms’ performance. In

order to estimate firms’ future performance, some factors which are barriers to entry, the

number of firms that get involved in the industry, their size and distribution systems, the level

of product differentiation and the overall elasticity of demand for the product should be

considered carefully. Another perspective also based on the above dimension, due to firms’

conduct being determined by industry structure, in the process of estimating firms’

performance, researchers “could ignore conduct and look directly at the industry structure in

trying to explain performance” (Porter, 1983: 176). This framework also considers how

public policies may affect firms’ structures and strategies. It is clear that the SCP approach

strives to explain and estimate the effects of market structure and conduct on the performance

of firms in an industry (Van Cayseele and Van Den Bergh, 1999; Lopez, 2001).

18

Figure 2.2.1: The basic SCP model (Source: Adapted from Porter, 1983:176)

There are a number of contrary schools of thoughts about the problematic aspects of the

SCP framework and disagreement about the idea of predicting performance mainly based on

industry structure (Phillip, 1976; Clarke, 1985); these groups argue that the IO framework is

stark and built on a limited number of factors related to industry structure (such as entry

barriers), whereas factors that affect competition and performance in industries could depend

on how business strategies are shaped and conducted.

2.2.3.2. Strategic group theory

The literature on “strategic groups” has generated an ongoing debate amongst scholars

and practitioners (Panagiotou, 2005; Lawless et al., 1989; McNamara et al., 2002). The

above two mentioned theories (RBV and IO) can be used to explain the nature of how

strategic groups were constituted. Both RBV and IO theory have shaped and provided a good

tool with which strategic management researchers can compare and contrast groups of firms

(Leask and Parker, 2006). Cool and Schendel (1987) found that the combination between

firms’ characteristics, environmental factors and strategic choices may shape company

performance. Fiegenbaum and Thomas (1995) indicated that by breaking the industry into

smaller groups of firms, forming them into the same strategic groups and looking at their

associated actions or their performance, the firms in that group can use these valuable

characteristics as a reference when making their own strategic decisions and it can be seen

that those who make “similar invesments are more likely to have similar drivers of

profitability” (Michael, 2015:201).

There are two perspectives of competitive strategy which are normally explored by

strategic researchers: resource pattern and strategic scope commitment; it can be seen clearly

that industries possess many segmentations, and many firms enjoy multi-segmentation, while

some firms serve only one segment (since they are heterogeneous in term of possessed

resources and used strategies). Firms having similar resources and scope characteristics can

be demonstrated; Leask and Parker (2006) and Porter (1980:129) define a strategic group as a

group of corporations that employ the same or similar strategies in a specific industry. The

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term “strategic groups” was mentioned by Hunt (1972) who sought to identify configurations

based on observing firms’ behaviour in the US home appliance industry and then explain

their differing performances. He supposed this group enjoyed the same characteristics which

related to “cost structure, formal organisation, control systems, management rewards and

punishment”.

Levy and Weitz (2008) indicated that “the retailing format refers to the structures for

sequencing and organising the selected retailing activities into coherent processes that fulfill

the customer experience. Specially, the format represents a combination of particular levels

of each element of the retailing mix, such as product assortment, pricing strategy, location,

customer interface, and so forth” (Sorescu et al., 2011:S5).

As Porter discovered, individual strategic group members face similar threats and

opportunities in the competitive market. A strategic group might include only one or more

members (Müller-Stewens, 2005). A further definition provided by Porter (1979), Cool and

Schendel (1987), is that a strategic group is seen as “a set of firms competing within an

industry on the basis of similar combinations of scope and resource commitments”, these

firms follow similar strategies “in terms of the key variables and competing with each other

within an industry”, and that they share “similar strategic logics and dimensions”. These

dimensions can be brand identification, specialisation, price policy, channel selection,

technological leadership, product quality, vertical integration and cost position (Porter, 1980)

Mascarenhas and Aaker (1989) indicated that mobility barriers (barriers to entry and exist)

can differentiate between groupings of businesses. In that, mobility barriers impede the

movement flow of firms in the same industry from one strategic group to another (Caves and

Porter, 1977). A strategic group owning high mobility barriers is more insulated from

competitors and has a stronger bargaining power (Porter, 1979).

A firm’s strategic choice can be divided into three classes: doing better at their current

group, moving to their favourably targeted group (Porter, 1980) and creating a new strategic

group (Duan and Jin, 2014). It is conceived that moving successfully to other groups is

extremely difficult and the majority of firms would probably not be able to move to a target

group in the short term. In addition, performance is constituted by many factors, and

members of the same strategic group can experience them differently; a high average

profitability “does not mean that every member in the group performs well” (Cool and

Schendel, 1988, Porter, 979). Therefore, moving to other groups may not be a feasible choice.

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Strategic groups demonstrate a real picture of industry competition and many firms and

competitors can fall into different competing clusters (Reger and Huff, 1993). It helps

marketers and strategic managers to better understand the complexities of the competitive

landscape in the industry and strategic groups which they belong to. In fact, companies in

specific industries often differentiate against other companies via a number of factors such as

used distribution channels, the market segments they serve, product quality, technological

leadership, customer service, pricing policy, R&D cost, advertising policy and promotion.

Based on the above differences, it can be observed that many groups of companies have been

appearing as a cluster with each member in that group pursuing a similar strategy – a strategic

group. Therefore, strategic group includes competitors with similar conditions, competitive

approaches in the markets, similar market position, structure and competitive beliefs. There

are some basic characteristics of strategic groups which are mentioned by many researchers:

firms have a tendency to compete mostly with other firms in same strategic groups because

they all have similar resources (Cool and Schendel, 1987; Dranove et al., 1998), “strategic

group members operate on comparable strategic dimension” (Adejuwon, 2014; Porter, 1979;

Peteraf and Shanley, 1997, Ferguson et al., 2000); the performance of firms in that group is

likely to be similar (Cool and Schendel, 1987; Barney and Hoskisson, 1990); group members

are likely to react similarly to any opportunities and threats arising (Panagiotou, 2007).

Therefore, managers’ perceptions of their rivalry are formed by a group structure, rather than

looking at each firm’s competitive action.

The notion of strategic groups can be utilised to evaluate the positioning strategies of

firms; it enables firms to undertake an arguably more insightful investigation of the industry,

its competitive behaviour between groups, and to analyse the group’s structure. Besides that,

firms can clearly realise the number of possible and effective strategies that other competitors

used in order to succeed (Reger and Huff, 1993) and those who are intending entering into

the industry can easily find a place to insert their businesses as well as competing effectively

from the start. In other words, strategic groups include firms pursuing the same positioning

strategies (cost leadership/differentiation/ focus or combined strategies); at the same time,

they serve the same or relatively similar target groups of customers. Therefore, as a result, the

key factors for success (KFS) might be similar, they also face similar opportunities and

challenges in their business context (Panagiotou, 2005, 2006a). However, empirical studies

have produced equivocal evidence about the relationship between different strategic groups

21

chosen and their performance. Therefore, it is difficult to formulate advice on which groups

that firms should consider entering into (Leask and Parker, 2007).

However, other researchers gave completely contrary ideas about what factors should be

used to form strategic groups.

There are many tools to recognise where and which strategic group a specific firm

belongs to, the so-called strategic group mapping. The first step is to examine the firm’s

position against five competitive forces (Porter, 1980), looking at the power of buyer and

supplier, the competitive ability of that firm among competitors as well as competitive level,

how new entrants affect firm’s business and the threat of substitutes. These findings will

formulate firm’s strengths and weaknesses. The next step is to explore firms’ competitive

advantages based on firms’ positioning and its own resources. Firms having the same

strengths and weaknesses at the same competitive environment might react similarly toward

any changes. Then, looking at strategies used by the firms: their competitive advantages,

business structure, development orientation and goals; if these dimensions are similar, they

should be placed in the same strategic group (Feka et al., 1997).

Moreover, if firms develop the same strategic dimensions with the same level, including

the level of diversification, the degree of vertical integration, distribution channel, market

segmentation, expanding orientation and so forth, they also should be named in the same

strategic group (Feka et al., 1997). In that, strategic distance, which was first introduced by

Porter (1979), describing “the degree of dissimilarity among firms’ strategies” and

differentiating “their relative positions within strategic groups” (Duan and Jin, 2014:1860)

should be considered during the analysis process.

Porter (1980) introduced the Strategic Group Map (figure 2.2.2). He indicated many

strategic dimensions and mapping strategic groups as shown in figure 1 as taking two

dimensions and comparisons at a time. Then, McNamee and McHugh (1989) adapted and

named it the “Group Competive Intensity Map” (GCIM) which clustered firms based on both

“strategies used” and “its structure” (Figure 2.2.2); the structural and strategic determinants

which were considered include company ownership, company activity, degree of

specialisation, company size, company pricing strategy (Figure 2.2.3). For example, firms are

grouped based on companies’ pricing strategy and most important customer type (Figure

2.2.4).

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Figure 2.2.2: Ilustrative map of the US chain saw industry

(Source: Porter, 1980:153; McNamee and McHugh, 1989:90)

Figure 2.2.3: Average net profit before tax for market specialisation and company

ownership

(Source: McNamee and McHugh, 1989:90)

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Figure 2.2.4: Average net profit before tax for company’s pricing strategy and most

important customer type (McNamee and McHugh, 1989:96)

Here is the example of mapping strategic groups in the Fashion industry (Bonetti and

Schiavone, 2014) (Figure 2.2.5), they also shed light on some main features of the identified

strategic groups including design, manufacturing, branding and distribution.

Figure 2.2.5: Strategic groups scheme

(Source: Bonetti and Schiavone, 2014:64)

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In this research, the instruction of identifying a strategic group in the Vietnamese

supermarket industry will be investigated fully in Section 2.3.

2.2.4. Competitive positioning and competitive analysis

Over the years, researchers have been using the concept of strategic groups to investigate

firms’ competitive behaviour/reaction (Smith et al., 1997; Peng et al., 2004; Park and Yoo,

2016) and competitive positioning (Flavian and Polo, 1999; McNamara et al., 2002). Park

and Yoo (2016:684) stated “a firms’ competitive reaction should be understood as a series of

managerial actions over time” and their research indicated that firms indeed react to each

other. Giaglish and Fouskas (2011:1257) found “perceptions of competition intensity,

substitution threats and increased buyer powers are associated with broader and more

innovative competitive reactions”. Competitive reaction can be a part of analysing

competitive positioning (Horta and Camanho, 2014). Competitive positioning refers to firms’

relative posture in terms of the competitive space where firms are currently operating (Kale

and Arditi, 2002; Horta and Camanho, 2014). In other words, Fleisher and Bensoussan

(2007) defined competitive position of an organisation as “the position of an organisation

compared to its competitors in the same market or industry” (Viet and Yeo, 2017:20). There

are some ways to define competitive positioning in a specific industry, but the most

applicable accepted approach has been from Porter (1980) which categorises mode and scope

of competition. Mode of competition refers to the way in which firms achieve their

competitive advantages (i.e. via innovation, time, cost or quality) while the scope of

competition refers to the breadth of firms’ operation (i.e. scope of offered products/services,

narrow or broad market approach). Then, many researchers examined competitive positioning

based on the previous theories, such as McGee and Thomas (1986), Dikmen et al. (2009) or

Lahti (1983) who characterises competitive positioning using the size and nature of product’s

variables. Ramsler (1982) used size and geographic scope variables in the banking sector.

McNamara et al. (2003) found that differences in performance within strategic groups exist

due to different firm’s competitive positioning.

There are some analytical methods often being deployed to measure and identify the

competitive position of firms, such as Porter’s Five Forces; Strengths, Weakness,

Opportunities and Threat analysis (SWOT analysis); McKinsey Matrix; the Boston

Consulting Group (BCG) matrix (Dyson, 1990) but the BCG matrix is predominantly used in

competitive positioning compared to others (Viet and Yeo, 2017) (Figure 2.2.6, Figure 2.2.7).

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The following figures indicate a brief review of these approaches; it will be explored in detail

with direct application to the Vietnamese supermarket industry in section 2.4.

Figure 2.2.6: BCG matrix (Adapted from Porter, 1983:177)

Figure 2.2.7: Porter’s Five Forces Model – Fundamental determinants of industry

competition (Adapted from Porter, 1983:177)

2.2.5. Summary

The above is a review of some of the literature relating to strategic groups, including the

link between business strategy and firms’ performance, some background theories that have

shaped strategic groups, Resource Based View (RBV) and Industrial Organisation theory.

26

This is followed by a brief literature review of competitive positioning and competitive

analysis which is fully investigated. All of the above information can briefly describe and

explain the meaning of strategic groups and how they are constituted as well as partly

demonstrating insight into why strategic groups should be considered, since it can be noted

that different groups of firms might have different advantages and the term “customer

loyalty” might be defined differently between groups. This is considered as a fundamental

point leading to the necessity of this research. The next part is going to briefly review the

meaning of “Retail industry” which is one of the four main themes.

2.3. Retail industry

2.3.1. Introduction

In this section, retailing industry insight is going to be examined, including the retailing

concept, trends in the retailing industry, types of retailers, retail channels; followed by a brief

review of customer buying behaviour and some retail logistics issues.

2.3.2. Retail

2.3.2.1. Definition of retail and brief report on current global retail industry

There appears to be mutually inconsistent definitions of retailing among researchers

(Peterson and Balasubramanian, 2002; Dawson et al., 2008). Retailing is defined as “the set

of business activities that adds value to the products and services sold to consumers for their

personal or family use” (Levy and Weitz, 2004:6). Kotler et al. (2013:386) presents

“Retailing includes all the activities involved in selling goods or services to the final

consumer for personal, non-business use”. Researchers have argued retailing is not just about

selling products in store, it also involves the sale of services such as a home-delivered pizza,

overnight lodging in a motel, a videotape rental. Hassan et al. (2013:584) stated “retailing

begins as a local activity, which involves a transaction where the buyer intends to consume a

product” (Severin et al., 2001; Liao et al., 2008). Over the past few decades, there has been a

significant transformation of the retailing industry, consumers have gradually moved from

traditional shops to modern retailing channels (Morganosky, 1997; Hassan et al., 2013), many

newcomers and huge retailers penetrating the retail market have threatened and grasped the

opportunity of small local grocery stores (Hare, 2003; Gonzalez-Benito, 2005).

27

Figure 2.3.1 demonstrates the basic steps of a distribution channel; there remains a

question as to why manufacturers do not normally sell their products directly to consumers

At least part of the answer should result from a fuller understanding of the functions of

retailers. According to Levy and Weitz (2004), retailers hold many functions, including

providing an assortment of products and services, breaking bulk, holding inventory,

providing services.

Figure 2.3.1: Distribution Channel

(Source: Adapted from Levy and Weitz, 2004:7)

Picture of current global retailing industrys

Figure 2.3.2 presents “Top 250 quick statistics, FY2015” (Deloitte, 2017:4)

Figure 2.3.2: Top 250 quick statistics, FY2015

(Source: Deloitte, 2017:4)

28

The following figures present top 20 global retailers in 2014 (Deloitte, 2016:12) and top

20 global retailers in 2015 (Deloitte (2017:4; CEOWORLD Magazine, 2017) (Figure 2.3.3,

2.3.4). The full report provides top 250 global retailers in 2014 and 2015 (Deloitte, 2016;

2017). Looking through the lists below, store-based sales have overwhelmed e-commerce,

Walmart is still a king of the retail jungle followed by a warehouse club operator Costco with

$116.1 billion retail revenue compared to Walmarts $482 billion. “The majority of the largest

global retailers remain involved in the food sector. More than half of the 200 largest retailers

have supermarket, warehouse, hypermarket, or cash and carry formats, or some combination

of them” (Levy and Weitz, 2004:12; Deloitte, 2017)

Figure 2.3.3: The top 20 global retailers, FY 2014 (Deloitte. 2016:12)

29

Figure 2.3.4: The top 20 global retailers, FY 2015

(Source: Deloitte, 2017:17; CEOWORLD Magazine, 2017)

30

Geographic review

Figure 2.3.5: Global retail geographic analysis

(Source: Deloitte, 2017:24)

Asia’s grocery market is currently the biggest globally, with a predicted 6.3%

compound annual growth rate up to 2021. The region is estimated to reach US$4.8 trillion by

2021, the same size in terms of sales volume as that of Europe and North America

collectively (RetailinAsia, 2017).

2.3.2.2. Trends in the retailing industry

Over the past few decades, many new retail formats have been developed, consumers

can buy products via many platforms (both online and offline channels) or in many formats.

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For example, Tesco has developed their food retailing formats in the UK targeting different

groups of segmentations such as superstores, large supermarkets, Tesco Metro, Tesco

Express, combination gasoline and convenience stores, Tesco Extra and hypermarkets (Levy

and Weitz, 2004). Historically, retailing has been a local business. Stores were operated in

order to serve and fulfill the needs of the local community, and “retailing is now an

international activity” (Dawson et al., 2006:1). There are some reasons why some firms

choose to expand globally, whereas some others do not. For example, Wal-mart and France’s

Carrefour offer an amazing customer value through their efficient distribution and

communication system; McDonald and KFC attract their hungry customers everywhere they

are located. However, many retailers have also failed at attempts to expand their markets due

to different reasons such as wrong expansion strategies, misunderstanding market needs and

culture. According to Deloitte report (2016) with the title named “Global powers of retailing

2016: Navigating the new digital divide”, and Deloitte report (2017) with “Retail trends: The

art and science of customers”, the two reports indicated “We are living in the customer-

driven economy” (Deloitte, 2017:6). In previous years, research on the retailing sector

focused on globalisation (Levy and Weitz, 2004). Now, the retail trends for 2017 are focused

on three main areas.

“The first is changing preferences, including the trend toward

owning less and living in the social media-driven economy. The

second is changing retail formats through the blurring of sectors

and proliferation of on-demand fulfillment. The third is the

transformative possibilities from living with exponential

technologies, both in the store and beyond” (Deloitte, 2017:6)

These trends are not new but it is still interesting, retailers understand that technology

has moved to a fundamental issue and customers are finding new and surprising products and

experiences (Deloitte, 2017). With regard to preferences, retailers have now tried to fulfill

customers’ needs at different levels and have found their own niche markets. “Fewer, Better

Things” or “Less is more” is a slogan of Cuyana which is an e-commerce retailer located in

San Francisco (Fastcompany, 2016). As customers’ tastes have been changing, they prefer

products with good quality. Retailers have moved away from mass production or are showing

a tendency to shift away from fast fashion’s traditional business model, and create their new

32

programmes like “H&M Conscious” (Deloitte, 2017:6). Consumers define themselves by the

products they buy and experience they have. Thanks to social media, the trends and the

power of sharable retail experience have affected a loyal customer base. Besides the above

mentioned retail format, due to low barriers to entry, many “new retailers” make their

presence felt in retail markets as “pop-up” stores; the format of “order-by-phone” television

networks and e-commerce platforms has also become popular. In order to fulfill and serve

customers, one-hour delivery service, home delivery and order online pick up in store have

been introduced by many retailers such as Carrefour to create better customers’ on-demand

shopping experience (Deloitte, 2017). This process requires the partnership between

technology and delivery firms, traditional grocers and big retailers. For example, Sprout

Farmers Market cooperates with Amazon to provide fresh products for Amazon Prime

delivery in some specific areas.

All international activities can be related to the sources of goods for resale, the operation

of shops, and use of foreign labour and international expansion.

2.3.2.3. Types of Retailers

According to Levy and Weitz (2008), there are many approaches to categorise retail

format into different groups, but generally, it can be divided and summarised as follows

(Table 2.3.1)

Table 2.3.1: Types of Retailers (Adapted from Levy and Weitz, 2008)

2.3.2.4. Issues related to customer buying behavior

The behaviour of retail consumers has been explored in much previous research (Sinha

and Banerjee, 2004; Levy and Weitz, 2004; Prasad and Aryasri, 2011, Mukherjee et al.,

Food retailers General merchandise retailers Nonstore retail formats Service

retailers

Conventional

supermarkets

Discount stores Electronic retailing

Big Box food retailers Specialty stores Catalog and Direct-Mail

retailing

Convenience stores Category specialist Direct selling

Department stores Television home shopping

Drugstores Vending machine retailing

Off-Price retailers

Value retailers

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2012). According to Levy and Weitz (2004), there are three types of customer decision-

making process, including extended problem solving, limited problem solving and habitual

decision making. Extended problem solving is a purchase process that customers devote

significant time and effort to explore and compare products between many retailers due to its

estimated risks or uncertainty. Limited problem solving is a purchase decision process

referring a moderate time and effort involved due to customers’ previous experience, they

rely more on their personal knowledge about products rather than scrutinise all alternatives.

However, if competitors want to attract more customers, they might need to offer more

available information and service to get noticed and stimulate a purchase decision from these

potential customer groups by using prominent displays and creating a positive store

environment, or the so-called “impulse buying” (Mohan et al., 2013; Bellini et al., 2017).

Habitual decision making involves little or no conscious effort, “I will buy the same thing I

bought last time from the same store” (Levy and Weitz, 2004:110). The second issue relating

to customer buying behaviour is their buying process, there are five stages in the buying

process as selecting a retailer (Levy and Weitz, 2004:111) (Figure 2.3.6) It includes need

recognition, search for information about retailers, evaluate and select a retailer, visit stores

or internet site or look through catalogues, repeat store patronage if a successful purchase

decision has been made previously.

Figure 2.3.6: Stages in the Buying Process (adapted from Levy and Weitz, 2004:111)

34

The next issue is social factors influencing customer buying decisions. These social

factors include customers’ beliefs, attitudes, values and customer social environment which

are family related factors, reference group and culture (Levy and Weitz, 2008). All of the

above indicated elements create different choices between consumers.

2.3.3. Summary

This part has briefly reviewed the retailing concept as well as presenting information

about current top global retailers, geographical overview, followed by trends in the retailing

industry, types of retailers, retail channels; finally, issues related to customer buying

behaviour were indicated. The purpose of this part is to demonstrate an insight into the

current situation of global retail markets as well as types of retail channels and retailers. The

next part is going to explore the Vietnamese retail industry.

2.4. The Vietnamese retail industry insights

2.4.1. Introduction

This section will demonstrate the whole picture of the Vietnamese retail industry,

particularly supermarket format. From the beginning, the section is going to present an

overview of the Vietnamese retail industry, its current situation as well as M&A activities,

followed by an investigation of the Vietnamese traditional retail channels, and e-commerce in

Vietnam. Then, this chapter will present PESTLE analysis, industry life cycle and the five-

force analysis in order to clarify the current competitive environment of the Vietnamese retail

industry. Finally, drivers of change in the retail industry in Vietnam will be investigated.

2.4.2. Overview about the Vietnamese retail industry

Vietnam’s retail market is characterised as being one of the most dynamic markets in the

region with high annual growth rates. Hanoi and Ho Chi Minh City have been ranked

amongst the top 10 Asian cities for retail expansion in 2014 (Tuoitrenews, 2014). With a

population of more than 93 million people, about 70 percent of them aged from 16 to 64 is a

factor in the potential growth of the retail industry, this figure is also described as the

“Golden retail index” (Oxford Business Group, 2017) and Vietnam was placed sixth in the

2017 Global Retail Development Index (GRDI) (Vietnamnet, 2017). Per capita income has

been rising, the rate of urbanisation is high, living conditions have been improved, the

35

economic environment is stable and corporate income tax tends to decrease; sixty per cent of

the population are aged under 35 and have a vibrant interest in global trends and brands, the

average Vietnamese income has risen from US$433 to US$ 2200 per year in just five years,

which enables Vietnamese consumers to afford products and services from international

brands. “The World Bank has forecast that Vietnam’s $200 billion economy is likely to grow

to a trillion dollars by 2035, with more than half of its population, compared with only 11

percent today, expected to join the ranks of the global middle class with consumption of $15

a day or more” (RetailinAsia, 2017). These facts make the Vietnamese retail industry more

attractive in investors’ eyes. In particular, Ho Chi Minh city, Ha Noi, Hai Phong, Da Nang,

Dong Nai, Can Tho, Nha Trang can be considered as potentially significant developed areas

where income has presented much higher than the national average - about two to three times

higher. In fact, Vietnam’s urban middle-class is a target group for most modern retail chains

(Le, 2016; Vo, 2017). In addition, the current low retail density in Hanoi and Ho Chi Minh,

remains at a modest level of 0.26 and 0.12 m2 of retailer/ per person respectively, and is

significantly lower than other cities in the region such as Bangkok, Singapore and Kuala

Lumpur (HANOITIMES, 2017). Vietnam has a variety of retail channels including

traditional markets such as wet markets, flea markets, small independent grocery shops;

modern channels such as hypermarkets, supermarkets, shopping malls, department stores,

convenience stores, and e-channels (Dao, 2016). In Vietnam, small independent grocers and

wet markets are not large and well-equipped; they could not have an excellent-service-offered

as modern retail channels do but they are available at every corner of the market.

Figure 2.4.1: The population pyramid of Vietnam (Central Intelligence Agency, 2017)

36

Vietnam officially opened the retail market for foreign investors from 01/01/2009, before

that if foreign investors wanted a presence in Vietnam, they needed to cooperate with

Vietnamese firms to legalise their businesses. Thanks to having become an official member

of WTO in 2007, Vietnam has been able to fully open the door for foreign retailers to invest

in Vietnam. Under this agreement, from January 2015, foreign retailers are allowed to

establish their businesses in Vietnam with 100% foreign capital (Business Development

Group Vietnam, 2016). The retail market in Vietnam has been heating up since 2014, many

foreign investors have significantly penetrated Vietnamese retail market using mergers and

acquisition of local chains (Thailand investors; AEON (Japan), Emart (largest Korean

supermarket chain), Auchan (France)) and now compete directly with current domestic

supermarket retailers (RetailinAsia, 2016; Le, 2016). Smaller retailers who are unable to cope

with the new demands might run the risk of going out of business. More than that, foreign

investors have actively built their own distribution channels and expanded the number of

stores. These foreign retailers have many advantages in terms of capital and managerial

skills, but their most significant limitation is their level of understanding of local consumer

habits and Vietnamese taste. A lively picture of Vietnam’s retail markets in recent years

shows mergers and acquisitions (M&A), e-commerce, and fast-growth among some of the

new entrants. According to a report released by the Ministry of Industry and Trade (MIT)

(2017), foreign retail firms account for “17 % retail market share in shopping centers and

supermarkets, 70% in convenience stores, 15% in minimarts, and around 50% in online, TV

and phone sales” (Oxford Business Group, 2017).

Considering M&A activities, AEON from Japan (the largest retailer in Japan by sales

revenue) acquired 30% and 49% of local Fivimart (22 stores) and Citimart (27 stores)

respectively and renamed the stores to “Aeon Citimart” and “Aeon Fivimart” (The Japan

Times, 2015) and now have a presence in four malls in Vietnam (two in Ho Chi Minh city,

one in Binh Duong and one in Hanoi). They expect to invest in 20 further stores by 2020.

Vingroup, which is one of Vietnam’s leading conglomerates about involved in significant

property development and is a new player in the retail sector, acquired Ocean Retail Group,

Maximark and Vinamart and then established their own retail network named VinMart

(Nikkei Asian Review, 2016). VinGroups’s retail section was also crowned the fastest

growing retailer in Vietnam in 2016. Its retail network now consists of over 930 stores,

including 10 Vincom department stores, Vinmart supermarkets, Vinmart+ convenience

stores, Vinpro electronics stores, VinDS consumer lifestye specialty stores (Myhanoi, 2017;

37

Vo, 2017). They are considered to have strengthened the domestic retail sector in the face of

increasingly fierce competition from foreign players by applying many incentives in order to

improve product quality and hygiene standards, such as cooperating with local suppliers for

fresh fruit and vegetables and now offer premium quality at affordable prices. The vice

chairman of VinGroup has talked about the aims of their incentive programme being “to

promote domestic production and to build national brands with international standards to best

serve the local consumers” (VNExpress, 2016).

Many of Thailand’s conglomerates have penetrated the Vietnamese retail market; in

2016, TTC Group bought Metro Cash & Carry Vietnam, which is a wholesale operation

formerly belonging to METRO Group (a German owned company, including 19 stores and

related real eastate portfolio with a total value of US$704.1 million) renamed it MM Mega

Market Chain. Central Group, also from Thailand, acquired Big C Vietnam supermarkets (34

stores) (orginally owned by the Casino Group from France) at a cost of US$1.14 billion. In

2016 Central Group also bought a 49% stake in electronics retailer Nguyen Kim; this group

has also brought Marks & Spencer, Zara, H&M to Vietnam (VNExpress, 2016; Vietnam

Investment Review, 2016; VN Express International, 2016; Oxford Business Group, 2017).

Meanwhile, starting from 4 hypermarkets in 2012, Lotte Mart from South Korea had

reached 14 supermarkets by 2015 and is forecast to increase to 60 stores by 2020; E-mart,

which is South Korea’s leading retailer, invested US$ 60 million in a shopping center in north

Ho Chi Minh City. In 2015, Auchan (France) opened 3 stores under the “Simply” brand and

plans to reach 6 stores over the next few years. In addition, Takashimaya, a luxury Japanese

shopping center operator, has also established its first center (the Saigon Center) in Ho Chi

Minh City). This center is considered to be the main competitor of Vincom center (from

Vietnamese VinGroup).

Co.opMart is the leading food retailer in Vietnam with 33 supermarkets located in Ho

Chi Minh City and 51 stores across the country. Its owner (Saigon Coop) has also diversified

their retail network by developing more than 100 Coop Food convenience stores across Ho

Chi Minh city and offer many kinds of fresh produce.

In the north of the country, starting from 2006, the Hanoi Trading Corporation (Hapro)

had one department store and 21 supermarkets in many major northern cities such as Hanoi,

38

Thai Nguyen, Hai Duong, Thanh Hoa, Bac Can and Ninh Binh; by the end of 2015 they also

have 20 stores in Hanoi (Vo, 2017).

Convenience stores and mini-marts are the fastest-growing segment in Vietnam’s retail

sector. Circle K and Familymart entered the market in 2009 and have continued to expand

since. In particular, FamilyMart plans to establish more than 800 franchised stores by 2020,

7-Eleven entered the market in July 2017 and plan to expand to more than 1,000 stores in the

coming decade (Vietnamnet, 2017). “Convenience stores in Vietnam have become popular

destinations for young consumers to shop and hang out, as the stores provide them with an

air-conditioned environment, well-organised shelves and seating areas, high quality products

and, in some stores, free Wi-Fi”, according to the head of international grocery research

organisation IGD (RetailinAsia, 2017).

All of these factors have demonstrated a lively modern picture of the Vietnamese retail

sector and suggests that consumers will be likely to benefit from greater variety and choice

(Oxford Business Group, 2017).

There are currently approximately 800 supermarkets, 160 department stores and

shopping malls, 8.600 traditional markets, and more than 1 million family-run retail shops

across the country; it is forecast that the sector will double in the next four years, with the aid

of government-backed development plans. Many supermarkets are formed under different

strategic groups and formats: and while some of them are dominant compared to some others,

no single organisation can be responsible for more than 50% of the market, since these

markets are still considered to be a scattered industry, and a fragmented market (Nguyen,

2017; Oxford Business Group, 2017).

Vietnamese consumers are getting used to modern retail stores which can accommodate

changing needs with a greater variety of goods and services, instead of giving top priority to

traditional markets. Accordingly, the traditional needs for fresh produce might be gradually

replaced by a huge range of processed foods in order to satisfy the needs of the majority of

those who work full time.

According to Oxford Business Group (2017), Vietnamese retail turnover reached $117.6

billion in 2016, and sales rose 10.2 per cent year-on-year. This revenue growth rate was

relatively high compared to other markets in the region. Data from EuroMonitor International

showed that Vietnam’s consumer spending is about to grow 47 percent in the next four years

39

to $184.9 billion (VNExpress, 2017). However, supermarkets, convenience stores and

shopping malls accounted for 25 percent of total customer spending and this figure is

expected to rise to 45 per cent in the near future (2020). In addition, from 2015 to 2020,

Vietnam’s urban population is forecast to grow by 2.6%, one of the highest growth rates in

the region (RetailinAsia, 2016; Le, 2016). Unsuprisingly, food safety and hygiene have had a

significant effect on Vietnamese consumers’s food-purchasing decisions as many cases of

food poisoning have been reported. Customers have become more aware of food quality and

food origins. Customers of traditional retail channels do not know exactly where food comes

from (Vo, 2017). Therefore, the modern retail market in Vietnam has much further scope for

development. According to RetailinAsia (2017), the modern channel has been expanding

significantly and as predicted, the country will have about 1200-1300 supermarkets and more

than 300 large malls, and thousands of convenience stores by 2020. As reported by the HCM

Union of Business Association, Vietnamese goods used to account for 80-90% of the total

volume of sales in most retail channels. However, when foreign-invested retailers have

entered the market, foreign commodities assumed the dominant position and Vietnamese

producers find it difficult to present their products in foreign-invested retail networks

(RetailinAsia, 2017) due to the trade off between price and quality. “Foreign investors not

only dominate the retail market but also swap Vietnamese products off the shelves for their

own items”, reported by VNExpress (2016). To illustrate this situation, Vu Vinh Phu,

chairman of the Hanoi Supermarket Association (VNExpress, 2016) stated that:

“A bottle of vegetable oil sold in a locally-owned supermarket is always more

expensive than the same product sold in a foreign-owned supermarket”

Some popular retail brands in Vietnam are: Vinmart+, Circle K, Shop&Go, FamilyMart

(convenience stores), Ministop, 7-Eleven, B’s Mart; Vinmart, Big C, Co.opMart, Fivimart,

Citimart, Simply Mart (supermarkets), and Vincom, Aeon, Lotte, Parkson, Takashimaya

(shopping centers) (British Business Group Vietnam, 2016). The following table (Table

2.4.1) will present the numbers of supermarket in Vietnam:

40

Retailer Name and

Outlet type

Ownership No of

stores

Location Purchasing Agent Type

AEON Fivimart

Supermarkets

Share-holding

company, major

shareholders is

AEON (Japan)

and Fivimart (VN)

24 Hanoi Mainly from importers and distributors

AEON Citimart

Supermarkets

Share-holding

company, major

shareholders is

AEON (Japan)

and Dong Hung

(VN)

27 Mainly in Ho Chi Minh City Mainly from local producers,

importers and distributors

An Phu

Supermarket

State-owned

company

1 Ho Chi Minh City Mainly from local producers,


Big C

Hypermarkets and

Supermarket

100% owned by

Central Group

Thailand

34 20 cities and provinces across

country, including Bac Giang,

Binh Dinh, Binh Duong, Can

Tho, Da Nang, Dong Nai,

Hanoi, Hai Duong, Hai Phong,

Khanh Hoa, Lam Dong, Nam

Dinh, Nghe An, Binh Dinh, Phu

Tho, Quang Ninh, Thanh Hoa,

Hue, Ho Chi Minh City, Vinh

Phuc

-Dry foods and beverages mainly from

local producers, importers, distributors

and wholesalers.

-Direct imports of fresh and frozen

products (perishable food products)

- Own-produced products with BigC

labeled.

Co.opMart

Supermarkets

Local, its owner is

Saigon Coop (VN)

80 40 cities and provinces across

the countries

-Mainly from local producers,

importers, distributors and

wholesalers.

-Partly direct imports of food and

beverages.

-Own-produced products with BigC

labeled

Hapro

One departstore and

20 supermarket

State-owned

company

21 Hanoi and Nothern provinces Mainly from local producers,

importers, distributors

Intimext

Supermarket and

department stores

Joint-stock

company

14 Hanoi, Hai Phong, Hai Duong,

Nghe An, Da Nang

Mainly from importers and distributors

K-mart

Supermarket

Foreign-invested

company (Korea)

1 Ho Chi Minh City Mainly from local producers,


Lotte Mart

Supermarket and

hypermarket

Foreign-invested

company (Korea)

14 Ho Chi Minh (5), Binh Duong

(1), Dong Nai (1), Phan Thiet

(1), Da Nang (1), Vung Tau (1),

Hanoi (2), Can Tho (1), Nha

Trang (1)

-Mainly from local producers,

importers, distributors and

wholesalers.

-Direct imports of fresh and frozen

products (perishable food products)

Saigon Trading

Corporation

(SATRA)

Supermarkets

State-owned

company

3 Ho Chi Minh City -Mainly from local producers,

importers and distributors.

Sapomart

Supermarket

Hiway Co., ltd

Private-owned

company

3 Hanoi -Mainly from local producers,

importers and distributors.

Vinmart

Supermarket

Private-owned

company (VN)

80 Nationwide - Dry foods and beverages mainly from

local producers/ importers/distributors

and wholesalers. - Direct imports of

fresh and frozen products (perishable

food products).

Table 2.4.1: Main supermarkets in Vietnam

(Source: Global Agricultural Information Network, 2017:1013)

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2.4.2.1. Traditional retail channels: Wet markets, “Mon and Pop” small independent

grocery stores

As briefly reviewed from the beginning, traditional markets have been a dominant retail

channel in Vietnam despite the significant growth of modern retail networks. Vietnamese

consumers tend to go to wet markets, flea markets and “Mom and Pop” small independent

grocery stores for daily food and grocery shopping. Normally, these stores do not require

business licenses or a huge amount of capital to start up. “Wherever a new residential area is

built, a wet market is likely formed” (Global Agricultural Information Network, 2017:16).

These markets and stores mainly serve housewives who prefer to walk or use motobikes to go

to the nearest wet markets or “mom and pop” store to buy daily fresh produce and

consumables for families. They have been popularised in both rural urban areas when most

motobikers “stop by small stores along the streets to quickly purchase groceries rather than

having to park and line up at busy counters in supermarkets or modern convenience stores”

(Global Agricultural Information Network, 2017:16). There are currently approximately

8,600 traditional markets, and more than 1 million family-run retail shops across the country

(Nguyen, 2017; Oxford Business Group, 2017; Global Agricultural Information Network,

2017).

Table 2.4.2: Vietnam’s Grocery Retail Sales by Channel, trillion VND

(Adapted by Vo, 2017)

There are many reasons why traditional Vietnamese grocery channels have been

financially dominant compared to modern grocery channels. As noted, most supermarkets,

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hypermarkets and convenience stores are located in large cities and urban areas. Meanwhile,

70% percent of Vietnamese customers live in rural areas where modern channels are not

available. It takes time for consumers’ habits to gradually change from the traditional to the

modern. In addition, card payment for daily groceries used in Vietnam is not popularised,

consumers prefer paying cash and shopping quickly at traditional grocery retailers (Myhanoi,

2017). According to the latest Future of Grocery Report prepared by Nielsen, one-third of

Vietnamese consumers (34%) love shopping at hypermarkets, supermarkets and other

modern channels. Currently, in most large cities and urban areas, the strengths of

convenience stores and supermarkets lie in their convenience levels, which are not only about

location advantages but also about a variety of services or products offered, followed by

affordable prices and a customer-friendly environment (Myhanoi, 2017).

2.4.2.2 E-commerce

E-commerce is growing in Vietnam and sales are expected to grow 22 per cent to

account for 1.2 per cent of the total retail market by the end of 2017. According to the

Vietnam E-Commerce and Information Technology Agency (VECITA), the online shopping

trend is growing rapidly in Vietnam and it is forecast that 30 percent of the population will

buy goods and services over the internet by 2020. The report in 2015 on Vietnam E-

commerce stated that Vietnamese consumers spent about US$ 4.07 billion shopping online;

this figure is still comparatively small compared to other Asian countries, with China having

reached US$617 billion and South Korea reached US$39 billion (RetailinAsian, 2016).

According to Internet World Statistics, Vietnam is currently ranked 18th

in the world in terms

of the number of internet users with more than 54 percent of the population online. Many

famous e-commerce foreign-origin websites such as Lazada, Zalora and domestic ones such

as Adayroi.com, Thegioididong.com, Tiki.com and Sendo.com have joined Vietnamese retail

markets and provide consumers with a variety of fashion, electronic goods, books and even

food. Especially in large cities such as Ho Chi Minh, Ha Noi, Da Nang, Hai Phong, Can Tho,

there are thousands of small private online businesses operating via Facebook and other

social media channels selling their products online. In other words, people can sell and buy

everything they want via Facebook and websites; customers can pay cash when they receive

products (cash on delivery-COD- payment method) but there is no official data about the total

sales on these channels because there are still a number of private online businesses operating

without paying tax and dealing only in cash. Therefore, it is not easy to calculate the correct

43

sales revenue from this channel. Currently, some of Vietnam’s major supermarkets have

applied online selling channels which enable consumers to buy groceries online.

Figure 2.4.2: Vietnam’s urban population (The World Bank, 2017)

Ho Chi Minh and Hanoi are considered to be the main destinations for most investors

with high urbanisation percentages of 82.5% and 43% respectively and over US$2,500 per

capita income.

In 2016, 34% of Vietnam’s population was concentrated in cities, compared with 30.5 %

in 2010. It can be seen that most supermarkets are located in large cities, and that the

potential opportunity for investors who can easily access urban areas (rather than rural ones)

and extend their reach into previously untapped markets is significant.

2.4.3. PESTEL analysis- Industry life cycle and the five forces model

PESTEL analysis- Industry life cycle

Porter’s Five Forces and PESTLE analysis are considered as two sets of business tools

for facilitating analysis of the macro business environment in order to help firms recognise

their current situation and improve their competitive position in specific industries. PESTLE

identifies how various macro environmental factors might influence all activities of an

industry, and such analysis, can explain indirect effects on firms. It helps firms exploit

opportunities and evaluate markets and their potential development. On the other hand,

44

Porter’s Five Forces will give every single firm an understanding of the competitive

landscape and all leading forces inside the industry which affect their competitive standing.

PESTLE analysis includes: Polical, Economic, Sociocultural, Technological, Legal and

Environmental factors. Applying PESTLE analysis directly to Vietnam’s Retail Industry,

there are a number of factors being considered as follows:

Figure 2.4.3: PESTLE analysis (Haberberg and Rieple, 2008)

Political and legal factors can have a significant effect on the retail industry. Vietnam has

a stable political environment; there is no social unrest or action to provoke the current

government, issues relating to the political landscape and trade regulation have not changed

frequently, and the government has a reasonable development path for the Vietnamese

economy. Alongside its accession to the WTO in 2006 (effective in 2007), Vietnam has fully

opened doors in its distribution sector, thereby allowing 100% direct foreign investment in

many fields including commercial production and distribution. In many big cities, the legal

framework has focused on facilitating foreign and domestic investment allowing

development of businesses in food distribution, supporting them if they diversify into the

supermarket sector, accelerating the urbanisation process, gradually eliminating street

vendors and unofficial traditional markets. After careful consideration the government

ensures the retail industry develops as planned by proposing many strategies for specific

areas. In that, there will be plenty of goods ranging from consumer goods to food and

diversification simultaneously amongst all retail business models such as shopping malls,

45

supermarkets, convenience stores, hypermarkets, department stores and so forth. However,

corruption could be considered as a barrier for all investors as administrative procedures are

complicated and it takes a long time to deal with government due to their antiquated

managerial style.

Regarding economic factors, it can be seen that a retail sector will be strongly affected by

the economic environment. Thanks to rapid economic development and a relatively high and

stable GDP growth rate, the economy is growing (estimated 6.6 percent growth in 2017),

Vietnamese customers’ expenditure has increased significantly year-on-year, and industrial

competitive pressures could be reduced to some extent (Vietnamnet, 2017). Many investors

recognised this and there has been massive penetration into this sector. Besides that, as

indicated above, urbanisation also contributes to the development of retail industries. In

Vietnam, supermarkets or shopping malls have not traditionally existed in rural and poor

areas. Instead, people have official, unofficial and spontaneously-established traditional

markets. In respect of interest rates, any slight changes definitely affect the economy;

currently, the Vietnamese economy follows “market mechanism”, as interest rate changes

will lead to fluctuations in investment or spending. As interest rates decrease, the lower cost

of capital has led to investment increasing in many projects because most Vietnamese

projects are mainly borrowing-intensive; consumption has also increased as people are

reluctant to save when interest rates are low. Of course the opposite applies when interest

rates increase. Therefore, the interest rate is an effective tool for government in regulating the

economy. Besides that, with Vietnam’s retail market revealing its potential for development

and attracting many large foreign investors, the effect of currency exchange rates needs to be

considered: many foreign firms importing their products to sell in supermarkets and

shopping malls, will definitely see product prices and customer purchasing behaviour

affected by fluctuating exchange rates. Currently, the inflation rate in Vietnam has been

reduced, and has fluctuated in recent years around 2.5-5%.

46

Figure 2.4.4: Vietnam inflation rate (Trading Economics, 2017)

Regarding social and cultural factors, shopping at traditional and spontaneous markets

and buying food from street vendors is a habit amongst Vietnamese customers, and can be

regarded as a constituent of Vietnamese cultural identity. Vietnamese everyday food

preparation is sophisticated with the use of many varied ingredients. Vietnamese people have

a tendency to prefer buying ingredients in unprocessed and fresh form, to enable them to use

varied cooking techniques. All of their food requirements can easily be met at their traditional

markets with their location advantages. However, those who have regard to food hygiene and

product origin, and are prepared to accept fake or low-quality products with high-prices

might have gradually changed their purchasing behaviour and begun to move to

47

supermarkets, shopping malls or convenience stores. Besides that, many consumers prefer to

frequent shopping malls due to the variety of products and services offered. Unemployment

rates in Vietnam have decreased, living standards are improving, and consumers’ needs are

increasing at both quali and quanti levels. According to Statistic, Vietnam’s retail market has

grown 10.2 percent over the past year with total sales reaching $118 billion (VNExpress,

2017) and more than 85% of city dwellers prefer to shop at supermarkets or stores rather than

traditional markets. In addition, some households with limited shopping time on weekdays

might choose supermarkets for food purchase at the weekend. This is a big opportunity for

firms to explore and meet market demands.

Labour costs in Vietnam remain low, the general salary for normal supermarket such as

customer service or cashiers is about GB£150/month if they are official and full-time; part

time students or workers will be paid based on their total time of working, and normally it is

about 50p/hour. Many firms have identified Vietnam as a potential market with abundant

labour force and cheap labour costs.

With 70 percent of the population aged from 16 to 64 and high urbanisation rates,

Vietnam is gradually moving from “feeding and clothing oneself properly” to “creature

comforts”, especially amongst young citizens in cities. As the population pyramid of Vietnam

indicates, there are many different age ranges of consumers; firms need to consider their

localised demographic environment in order to meet their target customers’ needs as well as

offering the right products and price positioning to them. Customer power will be considered

in the next part (Five-Force analysis).

Currently supermarkets, shopping malls or convenience stores are mostly located in big

cities - firms ignore small towns and rural areas due to their lower purchasing power.

Besides, there are many additional reasons which can explain investors’ choices. Education in

big cities is generally better than elsewhere. In fact, education has been seen to influence

consumers’ behaviour: educated Vietnamese people living in cities are more concerned about

product quality and hygiene factors rather than price and convenience factors. They have

higher earning potential and independence in their expenditure, with enhanced needs and

longer shopping time. In some big cities, there are also huge differences in consumption;

immigrants and members of different social classes are consumers in the same marketplace.

Therefore, food firms have built their businesses in Vietnam based on their own development

strategies and the market segmentation that they are serving.

48

In addition, the proportion of males and females is not uniform across age groups (see

Figure 2.3.1). Generally it is women who make decisions as to which food and household

items are purchased because they are mostly responsible for cooking, and housework.

Vietnamese males do not usually cook, and women enjoy shopping more than men. This

factor should not be ignored as firms attempt to penetrate retail markets and plan marketing

campaigns.

Average income of people who live in big cities is much higher than elsewhere and there

is a big gap between rich and poor people in Vietnam. According to Tradingeconomics

(2017), in 2016, Vietnamese average income is 1,770 USD/year, and that of inhabitants of

big cities such as Ho Chi Minh, Ha Noi and Da Nang, Hai Phong is much higher.

Figure 2.4.5: Vietnam GDP per capita (Trading Economics, 2017)

Marital status and areas where people live affect retail business in many ways. Due to

high property prices in Ho Chi Minh City and Hanoi, and in line with traditional culture,

some couples live with their parents; this fact might influence food purchasing patterns.

Regarding technological factors, importing new technologies into business can be an

advantage for the organisation as well as its customers. It facilitates firms in improving the

stocking and distribution process. Technological equipment used in Vietnam’s supermarkets

or stores, including all computing systems that have smart functions are being designed to

align with supermarkets’ business models. Currently, all Vietnamese supermarket chains

have applied modern technologies in managing and controlling their back office and front

49

office activities. Technological factors are not seen as a barrier for all investors in Vietnam.

However, some supermarkets use low-quality software to manage their businesses in the

payment process which leads to customer dissatisfaction. In Vietnam, self-checkout or self-

service machines have still not been applied. Besides that, e-commerce in Vietnam has

developed significantly; 91% of customers own at least one electronic device, some of them

have used such equipment to purchase many products online. Retailers should develop and

expand their channels to meet customers’ needs (Le, 2016).

Considering environmental factors, people have an awareness about eco-friendly

products, recyclable packaging and any environmental effects during the production process.

Vietnamese consumers have mostly trusted brand names if they’ve decided to shop there; in

which case there should be no difference in purchasing behaviour. Besides, depending on

their budgets, their shopping styles will be different. If firms reveal their social responsibility

while doing business, cutting wastage, decreasing the use of natural resources and reducing

environmental damage, this will be more welcomed by Vietnamese consumers.

Vietnam’s retail market has many characteristics of a growth phase at the middle stage,

the industry has potentially brought profits to investors, firms can improve and increase their

market share if they have a good strategy which fits the macro and competitive environment.

Figure 2.4.6: Industry life-cycle (Haberberg and Rieple, 2008)

50

Analysing the competitive environment of Vietnam retail industry using Porter’s Five

Forces model

Figure 2.4.7: The Five Forces model (Haberberg and Rieple, 2008)

As indicated above, Vietnam’s retail market holds potential and there are a significant

number of buyers (consumers) who buy many products at supermarkets and stores. They

have a variety of choices in choosing the brand name and stores they will go to and they can

change to other stores and brand names easily without paying any significant switching costs.

Household products and consumer goods can be standardised or undifferentiated; consumers

can mostly find products anywhere (supermarkets, traditional markets and so forth). Besides

that, with abundant information about product quality, easy to access producer reliability

checking as well as many firms offering the same service, consumers in retail markets are

considered to having a high power. Currently, shopping malls in Vietnam rent a space in their

areas to other companies who want to sell some products inside the mall; these big customers

also have a high power, if supermarkets or the investors of that mall increase rent per square

foot or change their business policies (the number of events organised, marketing campaigns

etc.), their big customers might choose another mall depending on how much commitment

they have to their current location.

Regarding the power of suppliers for supermarkets or shopping malls and convenience

stores, they have low power compared to the firms because of the existence of other high

quality and abundant suppliers in the markets. Suppliers are always threatened by the

growing ability of other suppliers who offer firms a better deal. There are many suppliers for

51

supermarkets from processed food, household goods and electrical providers to fresh food

and vegetables, but it is not difficult to change and choose new suppliers. Therefore, both

supermarkets and their suppliers need to consider carefully any mutual policies.

According to Haberberg and Rieple (2008), there are three types of substitution in

analysing competitive environment. Considering retail markets, there are no products which

can carry out the same function as foodstuffs, but some alternative products can be

substituted for existing consumer goods; even in the area of food, there are plenty of

alternative food and drinks if consumers choose to change preferences. Music or drinks and

other items might fulfill similar psychological needs to some foods and consumer goods;

cinemas, holidays or buying a new bike might be considered as an alternative use of

spending power to buying goods in supermarkets. In retail markets, all products are regarded

as potential substitutes for different industries and categories. The examples above express

different levels of substitution and it is possible to reduce demand for a particular product, as

there is a threat of consumers switching to the alternatives (Porter, 1980). Therefore, there is

a significant threat of substitution in this industry.

Regarding the power of intensity of competitive rivalry, there are plenty of firms

participating and competing in Vietnam’s retail market to attract a higher market share; they

are from different strategic groups and different business formats. There are number of

dominant firms in the market, many new big firms having entered and created a new

competitive landscape in recent years. However, Vietnam’s retail market is identified as a

fragmented market, and the competition level is high.

Entry barriers influence the level of threat of new entrants in many industries. In

Vietnam, the grocery market has been transformed into supermarket-dominated businesses.

In the retail market, entry barriers are low, firms with strong financial status and good

managerial skills can easily enter this industry, the level of success depends on how well

organised the businesses are, and what strategies are used. This is because of the

fragmentation level of retail markets in Vietnam, and the many grocery business formats.

Therefore, the threat of new entrants is high.

Besides Five-forces, complementary products should be considered. In the automotive

industry for example, insurance and financial services casn be demonstrated to be

complementary products; while in the retail industry, all products and services offered by

52

other firms from different industries will be complementary products. Therefore, firms in the

retail industry who want to achieve sustainable development should consider this force.

Based on the above analysis of the macro and competitive environment, a picture can be

drawn of industry survival and success factors. All attributes that firms in the industry need to

have in order to make “an acceptable or exceptional financial return” are revealed.

2.4.4. Drivers of change in the retail industry in Vietnam

2.4.4.1. The government’s control

As mentioned above, after becoming an official member of WTO in 2007 and from

January 2015, foreign retailers were allowed to establish their businesses in Vietnam with

100% foreign capital (Business Development Group Vietnam, 2016). The whole retail picture

in Vietnam has changed dramatically with a huge number of foreign retailers penetrating the

market. According to Vietnamnet (2017), “The Government has allowed 100 per cent

ownership by foreign retailers since 2015, and favourable policy continues to usher them in,

as evidenced by the 12.5 per cent growth in foreign investment in 2016. A recently concluded

free trade agreement with the European Union is expected to further boost investments in

Vietnam”

Besides that, in an attempt to boost e-commerce, Vietnam is trying to convince 50 percent

of enterprises to set up their online stores and use e-commerce platforms to sell their products

or services. In addition, in order to increase non-cash transactions which are relatively

uncommon in Vietnam, the government requires all supermarkets, shopping malls and

convenience stores to accept payments via credit and debit cards (RetailinAsia, 2016)

2.4.4.2. Consumer behaviour patterns

As mentioned previously, Vietnamese consumers retain the habit of shopping for their

daily food and groceries in traditional retail channels, especially the older generation due to

many reasons related to price, culture and the nature of regions where they live as well as the

development level of those areas. However, modern retail channels still possess huge room

for development as numbers of people in urban and large cities have enjoyed shopping at

supermarkets, shopping malls and convenience stores.

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In addition, pricing has also been ranked as the most crucial decision-making factor

during the purchase. Going to supermarkets, Vietnamese consumers expect to obtain good

quality products at reasonable prices. Therefore, retailers should consider the price-quality

equation amongst their development strategies for doing business in Vietnam.

2.4.4.3. E-commerce

Online shopping for food and grocery products has been prevalent in Vietnam. There is

no data about how much money online customers have spent for food and products via online

channels, but more and more people these days have chosen foods and grocery as well as

other products online. In this research, the researcher will not concentrate thoroughly on

exploring factors affecting customer loyalty at e-commerce level. However, as a part of

research objectives, the researcher is going to investigate the relationship between how e-

service quality directly and indirectly influences customer loyalty.

2.4.5. Summary

This part has presented a panorama of the Vietnamese retail industry, including an

overview of the Vietnamese retail industry, its current situation, the current competitive

environment (via PESTLE analysis), industry life cycle and five-force analysis. Finally,

drivers of change in the Vietnamese retail industry in Vietnam were investigated. The next

part is going to present all literature around the main theme of this research: CUSTOMER

LOYALTY.

2.5. Customer loyalty

2.5.1. Introduction

According to Walton, (the founder of Wal-Mart): “There is only one boss - the customer,

and he can fire everybody in the company from the chairman on down, simply by spending

his money somewhere else” (Entrepreneur, 2017). The terms “The customer comes first” or

“The customer is king” are often used in business, slogans considered natural because firms’

final objectives are increasing their profits and image via customer satisfaction and customer

loyalty (Fornell et al., 1996; Qui et al., 2015; Bouzaabia et al., 2013). The following parts

will present many factors which might create customer loyalty.

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2.5.2. Consumer tastes, consumer habits, consumer preferences and consumer

behaviour

Retailers have realised that understanding their customers deeply can enhance loyalty

and their firms’ performance (Reed et al., 2000). Food choice is seemingly simple but in fact

it is a significantly complicated process of getting the right level of customer choice and

knowing the reasons why they choose it. According to Hawkins and Mothersbaugh (2007),

all marketing decisions are mostly made based on assumptions and knowledge of consumer

behaviour, Consumer behaviour demonstrates the picture of how people make decisions

about what they want, need, select and buy between different alternatives such as brands,

products and retailers. It is vital to understand customer behaviour in order to explore how

potential customers will respond to new products or services, and help firms recognise the

gap they need to fulfill in specific industries (Levy and Weitz, 2008).

Figure 2.5.1: Factors affecting customer behaviour

(Adapted from Levy and Weitz, 2008:123)

There are three factors affecting consumer behaviour: personal, psychological and social.

Personal factors explain differences between people within groups, the decisions they make

will be based on their individual characteristics, unique habits and interests. This factor is

informed by age, gender, background, culture and other personal issues (Levy and Weitz,

2008; Kopalle et al., 2010; Johnson et al., 2012). For example, older people will use their

money differently for daily spending compared to young people. Social factors lead to

different consumer behaviour. These include social class (income, education level, living

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conditions), and social interaction (the relationship at school, work, community). These

factors have a significant effect on how people respond to new products and marketing

messages as well as how a purchasing decision is made. Besides that, each customer will

respond and have different ways to respond to the information from marketers because they

have different mindsets, perceptions and attitudes, the so-called psychological factors. In

particular, consumers might change their needs and demands based on how they feel

personally. Besides that, customer behaviour is also shown when customers are

satisfied/dissatisfied with products or services, the frequency of repeat purchasing, and word-

of-mouth (Wong and Sohal, 2003). Customer behaviour can be affected by cultural variables

(Kopalle et al., 2010; Johnson et al., 2002). Customer satisfaction and loyalty can be different

between countries based on customer behaviour even though scholars use the same index.

The word “taste” can refer to many forms which result from how products are displayed,

prepared and cooked. Currently, supermarkets offer a huge range of fresh produce, own label

processed and branded food from various locations, along with their recipes. It can be seen

that food taste preferences are affected by the culture people live within. It leads to

constituting customers’ tastes and habits. Therefore, if firms wish to succeed, they need to

understand all factors contributing to taste and habit such as cultural factors, which are

believed to affect how firms structure themselves as well as shape their marketing strategies

(Johansson, 2000; Sudharshan and Mild, 2017). As Wright et al. (2001) note “food taste

preference has been closely linked to cultural development”. Hofstede (1980; 1984) identifies

culture as “the collective programming of the mind” which allow the differences between

groups to develop. The term consumer preferences is often used in marketing and it refers to

the likelihood of choosing one thing over another (Bruwer et al., 2011; Alphonce et al.,

2015). Pelsmaeker et al. (2017) showed that consumer taste is a key driver of consumer

preferences.

“Consumers’ preference for retail stores is affected by assortment, price offers,

transactional convenience and shopping experience” (Arpita, 2014:536; Miranda et al., 2005,

Lee at al., 2008; Carpenter and Moore, 2006). It is clear that consumer preferences have a

significant impact on consumer behaviour, and customer perceived value can potentially

affect customer behaviour which leads to their purchasing intention (Sirdeshmukh et al.,

2002; Li and Petrick, 2008). “From customers’ perspectives, gaining value and being

satisfied are essential consumption outcomes that influence buying behaviour and post

56

purchase behaviour (Keng et al., 2007)” (El-Adly and Eid, 2016:220). The research from

Alphone et al. (2015) showed that consumers are willing to pay a premium for both organic

and fair-trade produce. It is all about consumer preferences. These findings can be linked

with customer perceived value and it is supposed that there is a relationship between

customer preferences and customer perceived value. It is noted that preferences are

independent of income and price. Ability to purchase goods might not determined by a

consumer’s likes or dislikes. However, despite on-going research around consumer

preferences, consumer behaviour and customer perceived value, the current literature seems

to lack formative studies of how consumer preferences or demographic information affect

customer perceived value and satisfaction.

In this research, strategic groups/supermarkets where consumers choose to shop, age,

gender, location where they stay (5 main cities of data collection) and income will be used to

explore the relationship between constructs (customer perceived value, customer satisfaction,

customer loyalty). The hypotheses will be proposed at section 2.5.13.2.

2.5.3. Customer experience and customer perceived value

Customer experience

Customers have more power than ever due to a variety of available products and services

offered; the increasing competition in the marketplace has given customers more choices.

They do not just want to own or consume products or services; what they are looking for is

unique and memorable experiences (Pine and Gilmore, 1999; Grewal et al., 2009; 2017;

Lemon and Vehoef, 2016; Puccinelli et al., 2009; Kumar et al., 2013). According to Babin et

al. (1994) consumers evaluated a retail store in many ways which include stores’ functional

quality as well as its “emotional-induced quality”. For example, consumers visit

supermarkets not simply for food purchasing purposes but also for enjoyment and

entertainment. They will evaluate services and improve brand image as a result of how much

fun and enjoyment they have received (Srivastava and Kaul, 2016).

Customer experience is a subject which has been mentioned, researched by many

practitioners and researchers in recent times. It is a key strategic objective for firms (Johnston

and Kong, 2011). This term is firstly revealed by Holbrook and Hirshman (1982) who

indicate that elements of pleasure, beauty, symbolic meaning, creativity and emotion can help

firms understand better consumer behaviour. Pine and Gilmore (1999) stated that experience

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should be considered as the development of economic value and firms do not sell the

experience, they offer tangible facilities and intangible assets in their business environment

through which consumers can experience the services or products offered. It will be possible

for firms to control the customer experience as expected. In that, consumers always have an

experience as using products or service offered by firms, this experience can be regarded as

good, bad or indifferent. Pine and Gilmore (1999:89) also elucidated that “experience as

inherently personal, existing only in the mind of an individual who has been engaged on an

emotional, physical, intellectual, or even spiritual level”. The clear and comprehensive way

of explaining customer experience is defined by Gentile et al. (2007: 397) “originating from a

set of interactions between a customer and a product, a company or a part of the organisation,

which provokes a reaction. This experience is strictly personal and implies customer’s

involvement at different levels. However the concept of involvement is different from that of

customer experience”

From the beginning, researchers focused on the emotion of consumers at the time they

consume, interact with firms’ services, products (Holbrook and Hirshman, 1982). However,

there is no consensus about which factors constitute customer experience. Firms cannot fully

control customer experience via advertising, store displays, service interface, these

experiences might be influenced by other factors such as customer interaction and their

shopping purposes (Klaus abd Maklan, 2012; Meyer and Schwager, 2007, Hume et al.,

2006). Verhoef et al. (2009) describe experience as involving “cognitive, social, affective and

physical nature”. Consumption is not only the activity that occurs before and after

purchasing, it can be grouped into four stages including pre-consumption experience,

purchasing experience; core consumption experience and a remembered consumption

experience (Caru and Cova; 2003 and Arnould et al., 2002). Therefore, it needs to consider

the so-called “touch points” which is the process that customers actually get involved or

interact with firms in direct and indirect ways (Zomerdijk and Voss, 2010; Martin et al.,

2015, Lemke et al., 2011, Gremler, 2004; Juttner et al., 2013) (Figure 2.5.2)

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Figure 2.5.2: Application of the sequential incident technique to touch point research

(Source: Adaped by Stein and Ramaseshan, 2016:9)

Experience is something personal, unique and different consumers will definitely hold a

different level of experience (Schmitt, 1999; 2003). Many researchers have used their own

variables (Table 2.5.1) to looking at customer experience (Grewal et al., 2009; Verhoef et al.,

2009; Berry et al., 2002; Gentile et al., 2007; Naylor et al., 2008, Hsu and Tsou, 2011; Sheng

and Teo, 2012; Nasermoadeli et al., 2013) and regard it as a part of consumer behaviour.

Table 2.5.1: Summary of experience antecedent researches (Andajani, 2015:632)

There are some methods used to measure customer experience, the following table which

is adapted by Andajani (2015) (Table 2.5.2)

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Note: CEI (Consumer Experience Index); EXQ (Customer service experience)

Table 2.5.2: Experience Measurement Method (Adapted by Andajani, 2015:631)

According to Schmitt (1999), there are five different types of experiences to be

considered, which are “think, feel, act, sense and relate” and the marketers should integrate

all of these things to generate customers’ holistic experience and then Fornerino et al. (2006)

identified five dimensions of customer experiences including “sensorial-perceptual, affective

and physical-behaviour and social and cognitive (facets)”

Retail customer experience

Terblanche and Boshoff (2001) identified retail customer experience as all elements that

encourage or impede customers during the process of interaction between them and retailers.

Customer interaction can be activities about searching information, selecting stores to go,

purchase and post-purchase stages (Lucas, 1999; Wong and Sohal, 2006; Grewal et al.,

2009). The finding of Berry et al. (1990) stated that retailing is all about creating customer

experience by connecting with their emotions, emphasising reasonable price, saving

customers’ time and energy, giving them respectfulness. In the current competitive

marketplace, firms that offer a superior shopping experience tend to be more successful

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(Baker et al., 2002, Spena et al., 2012); Jones et al. (2010) propose that retailers can use

immersive technology to stimulate and energise customers’ shopping experience.

As mentioned above, many definitions about customer experience have been stated, and

retail customer experience can be defined as “the sum total of cognitive, emotional, sensorial

and behavioural responses produced during the entire buying process, involving an integrated

series of interaction with people, objects, processes and environment in retailing” (Shilpa and

Rajnish:792). Positive emotions are highly associated with a good shopping behaviour and

outcomes (Machleit and Eroglu, 2000). There are four dimensions which can characterise

retail customer experiences, namely joy, mood, leisure and distinctive, it is researched by

Shilpa and Rajnish, 2013 based on many variables which can affect customer experience

(Table 2.5.3)

Table 2.5.3: Items for scale development (Shilpa and Rajnish, 2013:794)

Despite the on-going conceptual development of customer experience and its constructs,

there is a limited number of studies investigating its impacts on customer perceived value,

customer satisfaction and loyalty (Lemke et al., 2011; Maklan and Klaus, 2011; Verhoef et

al., 2009, Bagdare and Jain (2013). However, many current studies about customer

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experience use the reflective method rather than applying formative approach. Some scholars

explored the link between customer experience and its outcomes such as customer

satisfaction and customer loyalty, ignoring mediating or moderating variables (Bagdare and

Jain, 2013). In the research of Lin and Bennet (2014), they found that customer experience is

positively related to overall satisfaction and the hypothesis that loyalty programme

membership positively moderates the relationship between customer experience and

customer satisfaction was rejected. Terblanche (2018) indicated that customer experience has

a significant direct impact on customer satisfaction. Therefore, whether the positive

relationship between customer experience and customer satisfaction exists is going to be

investigated in this thesis, the hypothesis can be seen in section 2.5.13.2.

Customer perceived value

Regarding customer perceived value, it has recently received significant attention in the

marketing field (Ulaga and Eggert, 2006) because it has a crucial role in predicting purchase

behaviour (Chen and Dubinsky, 2003; Chang and Wang, 2011) and contributes to firms’

strategy-adjustment, and it also constitutes customer loyalty in an electronic business by

decreasing the possibility of customer seeking alternative service providers (Anderson and

Srinivasan, 2003). And customer perceived value is a cornerstone of marketing and

competitive strategic research (Lindgreen and Wynstra, 2005: Khalifa, 2004). Past research

defined perceived value in a simple way as it refers to a trade-off between price and quality,

this concept is considered insufficient in modern marketing (Rintamaki et al., 2006) and then

it is re-defined by many researchers and marketers (Chen and Dubinsky, 2003; Chi and

Kilduff, 2011; Davis and Hodges, 2012).

Zeithaml (1988) introduced the concept of “perceived value” which is the relationship

between benefits and sacrifices, this term is assessed in terms of comparing between many

firms leading to the whole picture of “how buyers choose a certain product or supplier over

others” (Ulaga and Eggert, 2006; Anderson et al., 2000; Hanninen and Karjaluoto, 2017:

606).

Zeithaml (2000) defined perceived value as the overall assessment of customers toward

the products or services offered by suppliers based on what they received directly, in that

brand image, store attributes are also considered. In a similar vein, Leroi-Werelds et al.

(2014:430), Kotler and Keller (2009), Velimirivic et al. (2011), (El-Adly and Eid, 2016:220),

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customer perceived value is “a trade-off between what they get (i.e., benefits) for what they

give (i.e., price or sacrifice)”. The benefits component would include a perceived service

quality and a number of psychological benefits which competitors might not imitate easily

(Parasuraman and Grewal, 2000). The sacrifices components related to the form of monetary

and non-monetary prices (time, effort, energy) that consumers contribute at the purchasing

process. However, Sheth et al. (1991) stated that value perceived is not just quality and price

issues, it might also be affected by other social, emotional and epistemic factors.

Perceived value is developed based on “Equity Theory” (Yang and Peterson, 2004), those

who get involved in the exchange process might feel equally treated if there exists a good

balance about what is given and received.

There are two value perceptions which are considered in many literatures: functional

motives refer to tangible things such as price, quality, convenience; non-functional motives

(symbolic value) related to all intangible wants such as social and emotional needs (Chen and

Hu, 2010). Keng et al. (2007) indicated that perceived excellence value refer to what

consumers feel about the product performance and appreciate a service provider for all

professional and reliable service delivered. Therefore, service quality can be a good indicator

of a measure of customer values (Vera, 2015).

There are two theories used to explain perceived value: means-end chain theory and

economic theory of utility. Means-end chain theory is identified by Gutman (1982); it

explains how specific attributes of products or services (the means) are associated with

personal values (the ends). The theory suggested that customers are more likely to choose

products or services that closely obtain the consequences that they desire. This means that

customers will find the floors that can provide better values. Via this theory, marketers and

researchers will understand consumers and which factors affect perceived value. Especially,

the means-end chain theory is often applied in the food retailing industry and it helps firms

inform their business strategies (Devlin et al., 2003). The economic theory of utility presents

that customers will try to obtain maximum utility with minimum resources, such as time and

budget (Henderson and Quandt, 1958), these theories can explain customer perceived value

to some extent.

It is supposed that customer perceived value can potentially affect customer behaviour

which leads to their purchasing intention (Sirdeshmukh et al., 2002; Li and Petrick, 2008).

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“From customers’ perspectives, gaining value and being satisfied are essential consumption

outcomes that influence buying behaviour and post purchase behaviour (Keng et al., 2007)”

(El-Adly and Eid, 2016:220)

A number of measurements have been developed in order to measure “perceived value”,

the uni-dimensional measure (Patterson and Spreng, 1997; Cronin et al., 2000; Eggert and

Ulaga, 2002) has been applied by many researchers with a limited number of items that

represent a perception of value. However, the determinants of perceived value are different

among consumers (Sweeney, 2003). Boltom and Drew (1991) indicated the above

measurement has a lack of validity. Chang and Wang (2011:350) concluded that “customers

with a high perceived value have a stronger relationship between satisfaction and customer

loyalty than customers with a low perceived value”. In that, customer loyalty has been

regarded as one of the most vital factors contributing to firms’ profitability. If customer

perceived value is not understood thoroughly, the higher loss of customers would result as a

result of their dissatisfaction (Anderson and Srinivasan, 2003; Chiou, 2004; Tsai et al., 2006).

However, it needs to be noted that customers might be satisfied with products or services

delivered, but still not consider them good value (Petrick, 1999). Therefore, customer

satisfaction and customer loyalty are the two crucial factors revealing real customer perceived

values. In practice, many researchers have focused on the relationship between customer

perceived value and customer satisfaction/customer loyalty. Chang and Wang (2011) viewed

consumer loyalty (including repetitive purchase intentions and positive word-of-mouth

communication) as a dependent variable; customer perceived value and satisfaction as

independent variables when they researched online customers’ behaviour. The result

demonstrated a positive relationship between satisfaction - perceived value and customer

loyalty. It indicated “satisfaction has a higher impact on customer loyalty at higher levels of

customer perceived value (β=0.697, t=9.916) than at lower customer perceived value

(β=0.572, t=8.779)” (Chang and Wang, 2011:349). In addition, many researchers have

supported and found the positive relationship between customer perceived value and

customer satisfaction, in other words, customer perceived value is considered as a positive

and direct antecedent of customer satisfaction, such as El-Adly and Eid (2016), Babin et al.

(2007), Zameer et al. (2015), Ryu et al. (2008), Walsh et al. (2011), Lin and Wang (2006),

Tung (2004). However, in the findings of Ishaq (2012), he indicated that customer perceived

value is positively and directly related to customer loyalty. However, Bei and Chiao (2001),

El-Adly and Eid (2016) also found only the indirect relationship existed between these two

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variables. In accordance with previous studies, the hypotheses of whether customer perceived

value is positively associated to customer satisfaction and customer loyalty will be proposed

in section 2.5.13.2.

2.5.4. Consumer satisfaction

Consumer satisfaction is explored by many scholars, the notion of it stems from

consumption experience (Eklof, 2000; Fornell et al., 1996, Anderson et al., 1994;

Parasuraman et al., 1988; Mohajerani and Miremadi, 2012; Torres and Kline, 2013).

Kursunluoglu (2014:529), Oliver (1999) stated “Satisfaction is a degree of meeting the needs

at the end of a purchase”. Kotler and Keller (2009:789) defined customer satisfaction as “a

person’s feeling of pleasure or disappointment that results from comparing a product’s

perceived performance or outcome with his/her expectations” (Oliver, 1981; Tse and Wilton,

1988). Parasuraman et al., (1988) introduced the disconfirmation paradigm, they stated that

customer satisfaction is a post-decision experience in which customers will evaluate how

much that retailers could meet their expectations. Mittal and Frennea (2010:3) defined that

“customer satisfaction is a customers’ post-consumption evaluation of a product or service”.

The well-accepted definition in the literature is from Calder et al. (2013) who defined

customer satisfaction as an overall summary evaluation of consumption experience.

Therefore, the level of customer satisfaction depends on the gap between expectation and

perceived performance. It is also a good indicator of firms’ future performance, a crucial

dimension to long-term business success (Zeithaml et al., 1996; Sarlak and Fard, 2009;

Ashlay et al., 2010; Tuli and Bharadwaj, 2009; Lo, 2012), firms in the hotel industry will be

unable to compete with their competitors if they cannot satisfy their customers (Forozia et al.,

2013). And firms with highly satisfied customers will get higher economic returns (Yeung et

al., 2002). Dominici and Guzzo (2010) indicated that the cost of appealing to new consumers

is much higher than that of retaining the existing one, although keeping customers loyal is a

complex issue. Evaluating customer satisfaction has been the largest annual market research

spending that firms made (Wilson, 2002). In looking at customer satisfaction, firms can

recognise their strengths and weaknesses; if firms can fulfill their customer needs, they will

receive customer satisfaction in return and vice versa.

There is no officially accepted model or measurement scale being used for customer

satisfaction. It is recognised as an exploratory dimension rather than a comprehensive model

(Gilbert and Velourtsou, 2006). In food service, customer satisfaction can be measured by a

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variety of elements, namely service quality, hygiene, atmosphere and product quality (Yuksel

and Yuksel, 2002). In the research of Emery and Fredendall (2002), they indicated that in

restaurant services, customer satisfaction is significantly influenced by employee behaviour

in the interaction process between them and their customers (Hennig-Thurau, 2004; Wall and

Berry, 2007; Baker et al., 2013), in the retail industry, every department and employee should

focus on who their customers are and their requirements as they are more demanding in a

competitive marketplace (Asher, 1989)

Customer satisfaction can only occur in the case of customer services matching

customers’ expectation (meet or exceed) (Beran and Evans, 2010). In literature, there are two

approaches of customer satisfaction that are highly accepted. The first one is “the expectancy-

disconfirmation approach” which is defined by Parasuranman et al. (1988) and Zeithaml et al.

(1996). It is mainly based on the comparison between customers’ expectation and their actual

perceived experience. The second one is “the performance-only approach”, the level of

satisfaction is evaluated based on each time purchasing activities occurred (Oliver, 1997).

Many researchers have also classified customer satisfaction into two types: attribute

satisfaction and overall satisfaction. “Attribute satisfaction relates to customers’ satisfied

cognitive mindset with products or services offered by firms, “Overall satisfaction” is

regarded as “pleasurable fulfillment” which refers to the effective responses of consumers

toward an offered product or service (Chiou and Droge, 2006; Machleit and Mantel, 2001;

Oliver, 1999)

Asher (1989:93) mentioned various questions that customers might ask themselves to

determine whether services delivered can be considered satisfying (Figure 2.5.3), and “the

more knowledge we have of customers’ needs, the better we will be able to respond”.

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Figure 2.5.3: Some ways in which customers measure their satisfaction

(Asher, 1989:93)

La Londe and Zinszer (1987) divided customer service into three stages and in these

stages, customers will interact directly or indirectly with firms’ service (Figure 2.5.4)

Figure 2.5.4: Elements of customer service

(La Londe and Zinszer, 1987, Adapted by Negel and Cilliers, 1990:28)

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Krampf et al. (2003) mentioned a confirmation and disconfirmation paradigm by

comparing expectations and perceived performance which are considered as cognitive

constructs (Westbrook and Oliver, 1991).

Determinants of customer satisfaction

There is some research on which factors might affect customer satisfaction. According to

Fornell et al. (1996), three antecedents which are perceived value, perceived quality and

customer expectation have been revealed. Service quality has a strong positive effect on

customer satisfaction and loyalty (Bolton and Drew, 1991; Siu and Cheung, 2001; Cronin et

al., 2000; Athanassopoulos, 2000). The research applied in a retail store (Sivadas and Baker-

Prewitt, 2000) also presented that service quality affects satisfaction, and that loyalty is

influenced by both service quality and satisfaction.

Expectancy Disconfirmation Theory (Tse et al., 1990; Oliver, 1997) can be used to

measure customer satisfaction. The theory focuses on comparing perceived performance level

and customer initial expectations. If products or services delivered are worse than expected,

“negative disconfirmation” would be a result; if it is better, the result is “positive

disconfirmation” (Oliver et al, 1997).

The relationship between satisfaction and loyalty has been increasingly explored in the

literature, especially in the retailing industry (Yang and Peterson, 2004; Lam et al., 2004;

Chen and Tsai, 2008; Liu and Jang, 2009; Pan et al., 2012; Bouzaabia et al., 2013). Loyalty is

developed in three steps, including cognitive loyalty, emotional and intentional loyalty

(Oliver, 1999). After consumers compare their actual experiences with their expectations,

they might be satisfied with the service provider or not, and these factors will affect the level

of intentional loyalty (Anderson et al., 1994, 1997). The findings from Perez and Bosque

(2015:22) showed that “customer satisfaction significantly and positively affected customer

recommendation (β=0.59, p<0.05) and repurchase behaviours (β=0.82, p<0.05)”. Chang and

Wang (2011:346) also concluded that “customer satisfaction has a significant impact on

customer loyalty (β=0.84m t-value= 4.81)”. There are a number of other researchers

supporting the above results, such as, Rahman et al. (2016), Chen (2012), Bouzaabia et al.

(2013), Kim et al. (2004), El-Adly and Eid (2016), Liu et al. (2011), Chang and Yeh (2017),

Kitapci et al. (2013), Han et al. (2011b). Wong and Sohal (2003) investigated customer

satisfaction in the retail industry, and concluded that the greater degree of consumer

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experience satisfaction with retailers, the higher probability of them revisiting the retailers.

This finding is consistent with the study from Calvo-Porral and Levy-Mangin (2015) that

customer satisfaction is negatively related to customer switching intentions. However, some

researchers also prove that customer satisfaction does not equate to customer loyalty (Mutum

et al., 2014; Qui et al., 2015; Stan et al., 2013; Kumar et al., 2013). Particularly, “That is,

satisfaction leads to loyalty but that loyalty can only be achieved in the presence of other

factors (Oliver, 1999)” (Qui et al., 2015:92). In addition, according to Mutum et al.

(2014:947), satisfaction might not be the best predictor of customer loyalty and “the presence

(or lack) of switching barriers may be the reason a customer stays with (or leaves) a firm”.

Besides that, “there is evidence that satisfaction and loyalty are not always strongly

correlated” (Miranda et al., 2005; Baumann et al., 2012:149; Mittal and Lassar, 1998); these

scholars stated that in most studies weak association between customer satisfaction and

customer loyalty were revealed. Jones and Sasser (1995) concluded that “the only true

loyalists were the totally satisfied customers” (Baumann, 2012:149). In addition, Sivadas and

Baker-Prewitt (2000) found that satisfaction was found to have no significant direct impact

on store loyalty. Kumar et al. (2013:246) found the link between customer satisfaction and

customer loyalty “ is not as strong as it is believed to be and customer satisfaction is not

enough to explain loyalty”, Kumar et al. (2013:246) also concluded “the variance explained

by just satisfaction is rather small - around 8 percent”. These findings have left the above

relationship endlessly debated. The hypothesis related to whether customer satisfaction is

positively associated with customer loyalty will be proposed in section 2.5.13.2.

2.5.5. Perceived switching barriers

The relationship between perceived switching barriers, switching behaviour and

customer retention has been explored by many scholars in recent years (Jones et al., 2000;

Stant et al., 2013, Mutum et al., 2014; Liu et al., 2011; Tung et al., 2011; Koutsothanassi,

2017). It can be seen that consumer switching leads to decreased sales and market share as

well as increased costs that firms might need to spend in order to attract more new customers

(Terblanche and Boshoff, 2010).

Switching barriers have been explored widely in marketing literature (Mutum et al.,

2014) and there is no consensus between scholars as to its definition (Yang and Peterson,

2004; Tsai and Huang, 2007; Li et al., 2007). Switching barriers represent many factors

which provide additional costs to customers if they want to change to alternative providers

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(Jones et al., 2000). Also, Fornell (1992) and Tung et al. (2011) stated that switching barriers

include all reasons that impede and hinder customers from switching to competitors. The

existing literature has demonstrated two groups of switching barriers: positive and negative

(Han and Hyun, 2012; Han et al., 2011b; Jones et al., 2000). The positive switching barriers

based on relational benefits or loyalty programme benefits in which service providers have

invested time, money and effort in building a relationship with their existing customers,

creating commitment and emotional attachment to firms. Such benefits can be specially

targeted offers, social status improvement or confidence. Such benefits can deter customers

from moving to competitors due to the unavailability of offered benefits (Han et al., 2011 a,

b). The negative switching barriers apply to all negative reasons which present in a

relationship (Hirschman, 1970) such as non-monetary, monetary costs or all sacrifices which

consumers have to pay in order to move to other providers (Han et al., 2009), and switching

costs which are considered as negative switching barriers.

Consumers can easily compare information between different service providers, they

might switch to other alternative providers if there is no or low switching cost (Anderson and

Srinivasann, 2003; Terblanche and Boshoff, 2010; Valenzuela, 2012). Switching can be

considered as a possible route consumers may take if current service or product-providers

cannot satisfy them (Hsu, 2014). Perceived switching cost refers to the perception of

customers about money, effort and time associated with platform changing (Jones et al.,

2007). Shafei and Tabaa (2016), Lam et al. (2004) defined switching costs as the cost

involved in changing from one supplier to another, consumers tend to remain on the same

platform if perceived switching cost is high. For example, in a mobile phone context, various

costs associated with platform changing might impede customers in switching. These costs

can be extra spending for other devices which must be associated with the new device that

customers intend to buy; or time and effort that customers need to assimilate in order to use

new products, or perceived loss of past investment (Guiltinan, 1989). In addition, Lee et al.

(2001) argued that unsatisfied customers would not switch to other providers because high

switching costs occurred. According to Becker (1960); Farrell and Rusbult (1981), in their

research on employee turnover, they concluded that employees are less likely to switch jobs

if the switching costs increase. Porter (1980:10) identified switching costs as “one-time costs

facing the buyer of switching from one supplier’s product to another”. The nature of

switching costs varies across industries (Fornell, 1992).

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According to Bitner (1995), Burnham et al. (2003), Edward and Sahadev (2011), El-

Manstrly (2016), Al-Hawari (2014), perceived switching costs can be divided into three

groups: monetary costs, psychological costs and relational costs. The monetary costs refer to

the benefits lost in giving up the current providers (commission, past investment, benefits

from loyalty programmes) and cost to buy a new one from alternative providers. The

psychological costs related to customers’ feelings and attitudes toward their new choices, the

anxiety that occurs during the switching process due to uncertain consequences. Chen and

Hitt (2002); Wathne et al. (2001), Aydin et al. (2005), Lee et al. (2001) also call these costs

“procedural costs” or “information costs” which include economic risk costs, search and

evaluation costs, adaptation costs and set-up cost. The final cost is a relational one; it refers to

“personal relationship loss costs” with the supplier’s staffs or “brand relationship loss costs”

with their current brand (Burnham et al., 2003; Patterson and Smith, 2003). Due to the above

listed perceived costs of switching, the possibility of customers’ leaving has been reduced.

Some researchers concluded that dissatisfied customers do not exit the service platform due

to high switching costs (Beerli et al., 2004, Colgate and Lang, 2001).

Satisfaction might interact with other factors in the decision-making process. The

interactions between switching cost or alternative attractiveness and satisfaction can

determine continuance intention (Shin and Kim, 2008; Alderfer, 1969; Bansal et al., 2004). In

many cases, consumers are satisfied with products and services delivered, but if the cost and

benefits of switching are beneficial for consumers, they might be willing to switch to other

providers. Consumers with different levels of satisfaction might perceive the switching cost

value differently. For example, with those who are satisfied, the motivation to switch is low,

so the switching cost is considered as unnecessary and unwanted but for those who are

unsatisfied, the cost of switching to other service providers is regarded as necessary in order

to fulfill the needs that their current providers cannot meet (Hsu, 2014). Therefore,

unsatisfied consumers might be less sensitive toward switching cost compared to satisfied

individuals. Another factor to be considered is the attractiveness of the available alternatives

(AAA) (Jones et al., 2000). This AAA construct is positively related to exit and negatively to

loyalty (Ping, 1993; Rusbult et al., 1982). When the perception of AAA is low, customers

have a tendency towards retention and more loyalty due to low perceived benefits of

switching providers (Anderson and Narus, 1990; Colgate and Norris, 2001; Mutum et al.,

2014).

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Some evidence from previous research indicates that switching barriers are positively

associated with loyalty (Fornel, 1992; Ping, 1993; Aydin and Ozer, 2005; Shafei and Tabaa,

2016, Koutsothanassi et al., 2017). This factor is concerned as one of the most vital indicators

of customer loyalty. When switching barriers are high, the option to exit will be limited and

customers might have a tendency towards loyalty (Hirschman, 1970; Jones et al., 2007;

Mutum et al., 2014). De Ruyter et al. (1998), Qui et al. (2015:92) also found that “in the

industries characterised by relatively low switching costs, customers are less likely loyal

compared to service industries with relatively high switching costs”, they examine more

carefully the perceived service quality compared to customers with high switching cost

(Jones et al., 2000). Han et al. (2011a, b) indicated that negative and positive switching

barriers can moderate the link between satisfaction and switching intention. However, Lam

et al. (2004) did not demonstrate support for the above in his research. The view that

customer satisfaction is the main indicator of customer loyalty has been explored by many

scholars, Cronin and Taylor (1992) stated that customer satisfaction behaviour can lead to

loyalty, but loyalty cannot be guaranteed only by satisfaction, other factors should be

concerned, it is “switching cost” (Olivier, 1999).

Figure 2.5.5: The conceptual framework (Mutum et al., 2014: 945)

According to Mutum et al. (2014:947), “past studies on switching behaviour have failed

to distinguish between consumers at various levels of loyalty by assuming that they are all

similar” (see Figure 2.5.5). Another proposed model was researched by Qui et al. (2015),

Stan et al. (2013), Tung et al. (2012), Kim et al. (2004), Liu et al. (2011), Rosario and Foxall

(2006) and it investigated the relationship between switching barriers and customer loyalty.

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They found that switching costs which were assessed in terms of price sensitivity have a

strong, positive and direct impact on customer loyalty and it also moderates the link between

customer satisfaction and customer loyalty. In other words, “as switching costs increase, the

association between customer satisfaction and customer loyalty diminishes and also as

customer satisfaction increases, the effect of switching costs on customer loyalty decreases”

(Stan et al., 2013:1549). The same results were found by Han et al. (2011a,b), Jones et al.

(2000): “the negative association between switching costs and loyalty in that customers feel

locked in the relationship when they perceive a high level of switching costs” (Qui et al.,

2015:92). Lam et al. (2004) revealed switching costs positively affect customer loyalty in

terms of recommendation and repatronage. Koutsothanassi et al. (2017:434) concluded that

“the switching barriers explained more than 40 per cent of customer loyalty”. All of the

above findings were consistent with the previous research from Jones et al. (2000) that

“higher perceived switching costs and lower attractiveness of competing alternatives are

associated with higher repurchase intentions” (Tung et al., 2011: 32). However, on the other

hand, Burnham et al. (2003) explored the case of financial switching costs and found that

switching costs have the lowest influence on customer loyalty and the findings from Tung et

al. (2011:35) showed that “the relationship between the attractiveness of alternatives and

loyalty is not significant” and Kim et al. (2004) found the impact of switching barriers on

customer loyalty, but not much compared to the customer satisfaction dimension. In the

research of Calvo-Porral and Levy-Mangin (2015), they found that the attractiveness of

alternatives is positively related to customer switching intentions. Picón et al. (2014) stated

that satisfaction might determine the expected advantages and disadvantages of switching and

then turn to loyalty decision, they argued that when consumers’ level of satisfaction is high,

consumers will perceive higher opportunity costs or loss of satisfaction related to switching;

regarding alternative attractiveness, Ghazali et al (2016) demonstrated the perception that

alternative attractiveness most likely depends on satisfaction level. Yang and Peterson (2004)

argued that when the level of satisfaction with one provider is higher, consumers tend to

perceive a low attractiveness from other providers. However, there is no consensus about the

role of switching costs and alternative attractiveness in the relationship between customer

satisfaction and customer loyalty. Many researchers found switching costs and alternative

attractiveness as mediators in the relationship between customer satisfaction and customer

loyalty (Picón et al., 2014; Malzler et al., 2015; Chuah et al, 2017). However, the relationship

between customer satisfaction and switching barriers (switching costs and alternative

attractiveness) can be mutual. That switching costs and alternative attractiveness increase can

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influence the level of customer satisfaction. The higher perceived attractiveness from other

providers might decrease satisfaction levels, and if switching costs are highly perceived

customer perceived value might decrease and consumers tend to remain satisfied with current

providers; in other words, dissatisfied consumers might feel trapped and forced to remain

with current providers in the case of higher perceived switching costs.

Chuah et al. (2017) also found that alternative attractiveness significantly moderated

the relationship between satisfaction and loyalty while switching costs did not. Edward et al.

(2010), Jones et al. (2000), Lee et al. (2001), Yang and Peterson (200), Stan et al. (2013),

Kim et al. (2018), Chang and Chen (2009) found that switching costs moderate the

relationship between customer satisfaction and customer loyalty. However, Chuah et al.

(2017) when they could not find switching costs as a moderator in the above relationship

(β=0.002, p=0.687>0.05) and Qui et al. (2015) found the same result as investigating the case

of low-tariff hotels.

Kim et al. (2018) could not find alternative attractiveness is a moderator of the above

relationship. In contrast, Jones et al. (2000); Sharma (2003), Chuah et al. (2017), Wu (2011b)

where they found alternative attractiveness moderates the relationship between customer

satisfaction and customer loyalty. Therefore, it can be seen that there remains no consensus

among researchers in relationships (direct, mediating and moderating) between the above-

mentioned variables. Based on the above review, different results have been found by

researchers; therefore, this research is going to investigate whether positive direct

relationships between switching cost and customer perceived value/customer

satisfaction/customer loyalty exist and whether alternative attractiveness is negatively

associated with customer satisfaction and customer loyalty. The hypotheses will be proposed

in section 2.5.13.2.

2.5.6. Brand experience

In recent years, brands have become more than just a logo on products, they help firms

infuse many distinct values into their products and services in order to appeal to consumers.

According to De Chernatony and Riley (1998), brand is one of the most important assets that

all firms who want to achieve sustainable development should possess. Based on many

previous reliable findings, consumers are likely to pay more for the brand that they are

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committed to because they perceive many values that other providers could not fulfill or

imitate (Jacoby and Chestnut, 1978; Perssemier, 1959; Reichheld, 1996).

Brand experience is defined as “the sensations, feelings, cognitions, and behavioural

responses evoked by brand-related stimuli that are part of a brand design and identity,

packaging, communications, and environments” (Brakus et al., 2009:53; Lin, 2015:2254).

Another way of explaining brand experience can be “the customer experience that originates

from a set of interactions between a customer and a product, a company, or a part of its

organisation, which provoke a reaction. This experience is strictly personal and implies the

customer’s involvement at different levels (rational, emotional, sensorial, physical and

spiritual” (Gentile et al., 2007:397). The fact that customers encounter and interact with

touch-points such as the brand stores’ physical and non-physical dimensions will definitely

influence and shape their brand experiences. These brand experiences can be pitted at an

emotional level, which allow customers to differentiate between different brands (Brakus et

al., 2009; Sahin et al., 2011; Hagtvedt and Patrick, 2009). The notion of brand experience

was introduced by Holbrook et al. (1982). It will be created as customers encounter and use

the brand, share with others their feelings about the brand, check promotion programmes, and

events offered by that brand (Ambler et al., 2002). Iglesias et al. (2011), Ishida and Taylor

(2012), tested the linkage between brand experience and brand loyalty, and identified three

aspects of brand experience which are sensory, behavioural and affective via research into

many industries (cars, laptops, mobile phones, televisions) and then Brakus et al. (2009)

propose two more dimensions, namely “cognitive and social”. Sensory experience refers to

consumers’ senses of sight, hearing, smell, taste and touch. The behavioural dimension refers

to physical and bodily experiences (sleeping in a hotel bed). The affective dimension implies

all emotions and internal true feelings, sentiments of customers towards the brand (warm

welcome by retail stores’ staff). Cognitive experience includes all thoughts of customers

towards the brand. Social dimension satisfies customers’ needs by making them feel more

connected to the brand. (Brakus et al., 2009; Zarantonello and Schmitt, 2010). In these four

dimensions, sensory elements can be seen as the most important indicator of brand

experience (Barnes et al., 2014).

One of the most significant indicators of a successful brand is not lying about the number

of customers buying products once, but rather the number of repeat consumers (Jacoby and

Chestnut, 1978). Besides that, many marketing researchers have done much research around

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brand loyalty (Copeland, 1923; Cunningham, 1956; Ha, 1998) and revealed three vital

dimensions including attitudinal, normative and behavioural. Based on these dimensions,

Gouraris and Stathakopoulos (2014) demonstrated four brand-loyalty types: no loyalty,

inertia loyalty, covetous loyalty and premium loyalty. In this research, no loyalty means

people know the brand, but never buy anything from the brand, inertia loyalty refers to

consumers who do not find the brand favourable but they repeat purchase due to its

convenience and no commit to that brand, they might switch to other providers if needed.

Covetous loyalty implies a permanent emotional attachment to the brand and customers want

to own any products from that brand, but these customers might not make any purchasing

transactions due to its expensive price (Goldsmith and Pan, 2008). Finally, premium loyalty

applies to those who are committed, emotionally attached and repeatedly buy goods of the

brand.

There is little research on retail brand experience; retail brand is seen as “a group of the

retailer’s outlets which carry a unique name, symbol, logo or a combination thereof” (Zentes

et al., 2008:167), they are completely different from product brands. After interaction and

engagement processes, including pre-purchase, purchase and post purchase stages with many

activities delivered by retail brands, customers have their own experience and determine

whether they should stay with that brand or not (Bagdare and Jain, 2013). Ailawadi and

Keller (2004:338) argued that “retailers are obviously in an ideal position to create

experiences that may involve their own private labels, manufacturer brands, or not be tied to

a specific product but the store as a whole”. As Das et al. (2012:101) indicated “As a

shopper, we most often take the name of a particular retail store. If somebody asks us “where

are you going for shopping?” we do not take the name of the brand of the product which we

intend to purchase”. Retail brand relates to selling both merchandise (tangibles) and services

(intangibles). According to Mathwick et al. (2011) customers buy products not only because

of their good brand but also the experiential value that customers experience by the brand.

Customer experience is positively associated with brand experiences (Dabholkar et al., 1996)

and effectively managing customer experience can lead to customer loyalties (Grewal et al.,

2009; Verhoef et al., 2009).

There are a number of factors which can affect brand experience, including in-store

experiences (store design and service interface) (Kumar and Kim, 2014; Bonnin and Goudey,

2012), critical service experiences (Vazquez et al., 2001), shopping experiences (Borges et

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al., 2010; Singh and Prashar, 2014) and price and assortment (Baker et al, 2002). The

following tables can summarise many studies about retail brand experience (RBE) model:

Table 2.5.4: Variables used for the retail brand experience (RBE) model

(Khan and Rahman, 2015:63)

A comprehensive qualitative analysis from Khan and Rahman (2015) has given eight

dimensions of the retail brand experience, excluding number nine and ten in the above table

(customer satisfaction and brand loyalty) (Table 2.5.4) Kim et al. (2015), Ha and Perks

(2005), Khan and Rahman (2015:66), Ishida and Taylor (2012) verified that “retail brand

experience influences both customer satisfaction and brand loyalty”. There are a limited

number of studies (Mathwick et al., 2011; Bagdare and Jain, 2013; Ailawadi and Keller,

2004) investigating the above-mentioned relationship. Therefore, in this research, the links

between these dimensions will be investigated in the context of the Vietnamese retail industry

and the research is going to discover whether there is a positive direct relationship between

brand experience and customer satisfaction/ customer loyalty. In accordance with previous

studies, the hypotheses mentioned above will be proposed in section 2.5.13.2.

2.5.7. Service quality

Consumers tend to become more demanding these days as many firms get involved in

business. If firms cannot serve and meet their customers’ needs and wants, they will lose

them and definitely affect their profits and eventually fail (Rao and Kelkar, 1997; Yoo and

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Park, 2007). According to Berry et al. (1988), service quality is considered as a significant

variable which contributes to firms’ success. It has received much attention from market

researchers for years (Izogo and Ogba, 2015). Service quality related to all judgments made

by customers “who compare their expectations with the service they perceive to have

received” (Gronroos, 1984:38), this term having a close relationship and is usually mistaken

for the term customer satisfaction, it cannot be interchangeable, although they both are terms

which are used to compare the expectation of quality and the actual service offered (Hussain

et al., 2015). However, service quality is “an overall evaluation of the services and

satisfaction concerned with the overall evaluation of the experience with those services”

(Dauda and Lee, 2016:844; Geore and Kumar, 2014). Parasuraman et al. (1988:17) also

defined service quality as “the degree of discrepancy between customers’ normative

expectations from the service and their perceptions of the service performance”. In fact,

service quality is a vital element in creating and increasing customer satisfaction (Szwarc,

2005; Baki et al., 2009). More and more firms have stated that high customer satisfaction can

be traced back to good service quality (Szwarc, 2005). In that, management and employee

commitment has played a crucial role in service quality (Moshin and Lockyer, 2010).

There are three types of services being identified by many researchers: pure service

(firms interact with customers at service providing process, such as a restaurant, nursing

home); mixed service (firms interact with their customers at both face-to-face and back

office, such as commercial airline); quasi-manufacturing service (firms present no face-to-

face contact with their customers, such as telesales, credit card). In retail markets, firms sell

their products to customers, but simultaneously offer service to them and the service quality

is one of the most vital dimensions which can attract more customers if they perceive that

service to be beneficial. According to Steven et al. (1995) in research on customers at

restaurants, he stated that the perception of customers on service quality will be based on at

least two factors: what is provided and how it was delivered. There are differences between

services and goods in the way they can be perceived and evaluated (Zemke, 1992) (Table

2.5.5)

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Table 2.5.5: Differences between products and services (Zemke, 1992)

Basically, customers do not evaluate services simply based on the service outcome, they

also consider how services are delivered and they have judgment and comparison between

their expectation and the actual service offering (Zeithaml et al., 1990). The conclusion of

good service will be reached if the perceptions meet or exceed expectations and it will

become problematic if perceived service quality is below expectations (Ahmed and Shoeb,

2009)

The problem is that the quality of service is not easy to measure and evaluate

(Parasuraaman et al., 1988) while in the competitive marketplace, it is necessary to

understand how customers measure service quality (Bayraktaroglu and Atrek). From the

beginning, Perasuraman et al. (1985) introduced a PZB service quality model (Parasuraman,

Zeithaml and Berry) by using ten key categories named “service quality determinants” (see

Figure 2.5.6) and the after use factor analysis method to explore the scale of service quality

with the standard of good reliability and validity, the scale is defined using five factors and

22 service quality questions.

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Figure 2.5.6: Determinants of Perceived Service Quality

(Source Parasuraman et al., 1985:48)

Figure 2.5.7: Service Quality Model (Parasuraman et al., 1985:44)

There are five gaps indicated in the above SERVQUAL model (the gap theory) (Figure

2.5.7). Gap 1 is the discrepancy between customer expectation and management cognition,

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gap 2 related to the discrepancy between firms’ perception of customer expectation and

service quality specifications, gap 3 implies the discrepancy between service quality standard

and the actual service delivered, gap 4 refers to the discrepancy between provided service and

what is communicated externally and gap 5 is the discrepancy between expected service and

customer perceived service. Curry (1999), Luk and Layton (2002) stated that the gap model

can be considered as one of the best received and most heuristically valuable contributions to

the service literature.

In marketing, the approach dominantly accepted and used to measure service quality is

the SERVQUAL scale which was introduced by Parasuraman et al. (1988). This tool

compares customers’ expectations before using services and their actual perception after

services are delivered (Gronroos, 1982; Juwaheer, 2004; Antony et al., 2004; Gounaris, 2005;

Jiang et al., 2000; Mostafa, 2005; Wicks and Chin, 2008; Chen et al., 2007; Hu et al., 2010),

and Q (service quality) = P (perceptions) – E (expectations). There are five dimensions being

considered in the SERVQUAL model, including tangible, responsiveness, reliability,

empathy and assurance. A SERVQUAL score can be evaluated by each dimension above

(Figure 2.5.8)

Figure 2.5.8: Five dimensions of SERVQUAL model

(Parasuraman et al., 1985, adapted by Gupta and Chen, 1995, Lee et al., 2011)

Another school of thought indicated some deficiencies and inconsistencies of this model

due to its limited application in pure service settings such as health care and banking. They

analysed based on their own research topic (Cronin and Taylor, 1994; Finn and Lamb, 1991;

Johnson et al., 1995) and use their amended models, namely SERVPERF (Cronin and

Taylor, 1992) which has been confirmed by many scholars as measuring service quality and

customer satisfaction and the “Non-difference”concept (Brown et al., 1993). Babakus and

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Boller (1992) stated that dimensions of service quality should be considered in a specific type

of service. Mei et al. (1999) used the model HOLSERV which is developed from

SERVQUAL; in this model, they indicated three factors which can be used to evaluate

service quality, including employees, tangibles and reliability. Specifically, employees were

considered as the most important dimension. Dabholkar et al. (1996) proposed and developed

a Retail Service Quality Scale which includes five factors: “physical dimension, reliability,

personal interaction, problem solving and policy”.

Jamal and Anastasiadou (2007:38) stated that “despite significant interest in service

quality and its dimensions, very little research has investigated the effects of specific

dimensions of service quality on satisfaction and loyalty”. Kitapci et al. (2013) examined the

effects of specific dimensions of service quality on satisfaction and loyalty in supermarkets;

they found that “independent variables together describe 56 percent of customer satisfaction

variability” (Kitapci et al., 2013:248). Among the 5 dimensions presented in Figure 2.5.8,

empathy dimension was found to have a stronger connection with customer satisfaction than

the other four service quality dimensions; reliability dimension is not significantly associated

with customer satisfaction (Kitapci et al., 2013). Cronin et al. (2000), Dauda and Lee (2016),

Kim et al. (2004), Hsieh and Hiang (2004), Liu et al. (2011), Sivadas and Baker-Prewitt

(2000), Chang and Yeh (2017) found that there is a strong positive relationship between

service quality and customer satisfaction. And the studies from Bauer et al. (2006), Turel and

Serenko (2006) and Wang et al. (2004), Hsu (2006), Zameer et al. (2015), Jiang et al. (2018)

showed that service quality has a direct and positive impact on customer perceived value

which has been shown to generate loyalty. In this case, service quality might also indirectly

affect customer loyalty via customer satisfaction. In accordance with previous studies, the

hypotheses related to whether service quality is positively associated with customer perceived

value, customer satisfaction and customer loyalty will be proposed in section 2.5.13.2.

2.5.8. Corporate factors

2.5.8.1. In-store logistics and store image

There is a slowly growing body of literature exploring in-store logistics, in the so-called

“last 50 metres” (McKinnon et al., 2007), aiming to meet customers’ needs at store level by

assuring “demand-driven on-shelf availability” (Reiner et al., 2013; Fisher et al., 2000;

Kotzab et al., 2007; Kotzab and Teller, 2005). The in-store logistics process includes all flow

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activities from the unloading bay of a store onwards to storage, handling, transport, shelf-

stacking and replenishment, (including return services and disposal) (Gudehus and Kotzab,

2012; Kotzab and Teller, 2005). According to Samli et al. (2005), Bouzaabia et al.

(2013:112), in-store logistics operations include “handling, arranging, ordering and

processing of merchandise within the store”. The purpose of these activities is ensuring the

availability of products in stores; it plays a crucial role in retail stores because no product

available means no purchasing transaction occurs (Kotzab and Teller, 2005). Therefore,

“product presence can be regarded as one observable outcome of in-store logistics operation”

(Bouzaabia et al., 2013:116). Van Zelst et al. (2009) revealed the cost structure of one

European retail chain in his research: 45% of the cost is used for in-store logistics operation,

22% for transportation and 33% for warehousing. It cannot be ignored that “shelf

management” is an important part of in-store logistics; it refers to the job that always make

products available on the shelf by checking replenishment. In that, poor in-store logistics

means that products are not available during consumers’ shopping process, even though the

store has that product in stock. “Stock-outs” might affect customer satisfaction and customer

loyalty to some extent. Other dimensions of in-store logistics are product information,

shopping convenience, return services. It includes all activities which can facilitate customers

during the shopping process and post-purchasing, such as checkout lanes which can affect

waiting time; and available return services (Bouzaabia et al., 2013); effective in-store

logistics means offering “the quantities of products as requested by end-users at lowest cost

possible” (Kotzab and Teller, 2005:596). The two researchers also identified four in-store

problem areas: knowledge of cost and service levels, standardisation, qualified personnel and

store design.

Mou et al. (2017) identify three entities in retail store operation: customers, employees

and products and they explore the relationship between them (Figure 2.5.9). Customers

encounter products via purchasing, returning activities, employees can advise and give

suitable information about products or services to customers; products’ attributes, their

availability and employees’ behaviour have influenced customer experience and satisfaction

in many ways. In-store logistics activities reveal the constant interaction between these

entities, therefore the perfect combination between all the above factors will lead to effective

in-store logistics.

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Figure 2.5.9: Entities in retail store operation (Mou et al., 2017:402)

The following in-store logistics process is comprehensively presented by Kotzab and

Teller (2005) (Figure 2.5.10), it has been explained step-by-step and fully describes the

logistics operation within stores. There are eight steps in in-store logistics process. The first

step, “Delivery/receipt” occurs as products are delivered to stores from a distribution center;

store employees will take over and control the delivery with receipt. The second step refers to

“Transport I” with incoming products either being transferred directly to the shelves

(“Storage II”) or to the store’s storage area (“Storage I”-third step). In this third step, products

which are allocated specific storage areas can be re-packaged or split up into small units. The

next step named “Transport II”, products will be transported from the storage area to the

shelves. Then, the process of handling products; putting them on the shelves, shelf filling,

product presentation and inventory control are named “Handling/Storage II”. The next step,

“Processing of transactions” is where end-users pay for their purchasing activities. It also

relates to the seventh step -“Re-order”- via which retailers guarantee the availability of the

products’ flow (incoming and outgoing products in stores), in other words, these are

inventory activities. Finally, “Disposal/recycling” in which all damaged or broken products

will be either recycled or removed from the shelves.

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Figure 2.5.10: In-store logistics process (Kotzab and Teller, 2005:597)

All the above in-store logistics activities will enables consumers to find and purchase

product easily, affecting the customer experience, customer satisfaction and loyalty to some

extent (Kotzab and Teller, 2005).

Store attributes have played a vital role in generating customer satisfaction and loyalty.

Many studies have explored the role of store attributes in the retail industry. Based on their

research, “store atmosphere, store image, parking facility, lifestyle, merchandise,

convenience and location” should be considered (Finn, 2004; Nikhashemi et al., 2016: 433).

Du Preez et al. (2008) proposed eight dimensions of store attribute including promotion,

convenience, atmosphere, institutional, facilities, merchandise, sales personnel and service.

Baket et al. (2002) and Mohan et al. (2013:1713) also mentioned stores’ layout which “refers

to the way in which products, shopping carts, and aisles are arranged, the size and shape of

those items, and spatial relationships among them”. It is clear that most customers decide to

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buy some products in a specific supermarket due to its good store image (Hartman and Spiro,

2005; Saraswat et al., 2010). Store image can be defined as the personality of a store in

customers’ mindset (Burt and Mavromatis, 2006; Chang and Tu, 2005). According to De

Ruyter (1998:34), store image as “the complex of a consumer’s perception of a store on

different (salient) attributes”. In other words, Mafini and Dhurup (2015:1296), Saraswat et al.

(2010:168) defined store image as “the symbolic, experiential expression of the manner in

which consumers see or visualise a store”. It is an important driver of customer satisfaction

(Du Preez et al., 2008a) as it “provides value-added benefits to the shopper” (Saraswat et al.

(2010:169). It reflects the set of beliefs about stores’ relative attractiveness which are

perceived by consumers. These perceptions might be different across countries, market

sectors and store formats (Martineau, 1958; Burt and Mavromatis, 2006; Hirschman et al.,

1978). Amine and Cadenat (2003) identified three important noticeable cues that affect

customers’ perceptions about store image, namely the store’s appearance, employees and

promotional materials. In retail business, there are three explored dimensions about retailing

experience which directly relate to store image The first one called “physical environment”

refers to how a store is decorated, logically labeled, category arrangement and a good layout

that leads to consumers moving efficiently through stores, and how it enables customers

easily and quickly to find products (Titus and Everett, 1995; Richardson et al., 1996; Teller

and Dennis, 2012). Some stores create a convenient infrastructure by applying shopping

carts, signage and so forth or offering a variety of services which can facilitate consumers

during shopping time (self-service technologies such as self-checking the quantity of fruits

bought, self-check out machines and sales advice) (Bouzaabia et al., 2013). The second

dimension relates to the merchandise that a store sells (Bloemer and De Ruyter, 1988), the

third one refers to the interaction between consumers and store personnel (Baker et al, 1994;

Semeijn et al., 2004). Store image is different among customers and it reflects how customers

experience a store. Besides that, store image can also be created by word of mouth and

marketing programmes.

Much empirical attention has been placed on five dimensions of store image which are

store assistance, store atmosphere, store appeal, promotion and store accessibility (Mafini and

Dhurup, 2015). Besides that, location, parking facility, clean and spacious environmental

atmosphere, display features are factors investigated by Chen and Hu (2010), Jinfeng and

Zhilong (2009), Fung et al. (2013).

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As mentioned above, there are the link between store image and personal values which

feature in means-end chain theory (Gutman, 1982), and store image definitely affects store

choices and customer loyalty (Osman, 1973; Arons, 1961; Malhotra, 1983). The following

figure 2.5.11 being researched by Bouzaabia et al. (2013) can make all the above theories

clearer:

Figure 2.5.11: The relationship between in-store logistic, customer satisfaction and

customer loyalty (Bouzaabia et al., 2013:121)

In the studies of Bouzaabia et al. (2013), Poncin and Mimoun (2014), Carpenter and

Moore, (2009), Shobeiri et al. (2013), Sivadas and Jindal (2017), a strong association

between store image and satisfaction was found (see Figure 2.5.19) and there is a direct

positive relationship between in-store logistics performance and satisfaction. In addition, the

researchers also found that “the effects of perceived in-store logistics performance on

satisfaction are partially mediated by store image” (Bouzaabia et al., 2013:121). These

findings are consistent with the study from Samili et al. (2005), Arnold et al. (2005), Ltifi and

Gharbi (2015), Mou et al. (2017) who presented that in-store logistics can help customers

navigate the retail servicescape efficiently and effectively, via improving customer

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experience and satisfaction. Conversely the future patronage intention would be adversely

affected as customers experience the consequences of inadequate in-store logistics. However,

the research of Andaleeb and Conway (2016) revealed a contradictory result of store image

related to atmospherics not having a significant impact on customer satisfaction. In current

literature, the number of studies which have concentrated on investigating how in-store

logistics affect customer perceived value and customer satisfaction in different retail formats

is still limited, even though there are a number of papers exploring in-store logistics. In

accordance with previous studies, the hypotheses of whether in-store logistics have a positive

impact on customer-perceived value and customer satisfaction and whether store image is

positively associated with customer satisfaction will be proposed in section 2.5.13.2.

2.5.8.2. Store accessibility and loyalty

Store accessibility is regarded as customer perceptions about convenience location of

stores in terms of speed, simplicity and ease (Teller and Reutterer, 2008). There are well-

established variables which significantly influence store choice and switching behaviour

(Seiders et al., 2005; Gauri et al., 2008b), including “competitive intensity”- the number of

competitors in the industry (Sloot et al., 2005) and “distance to the next rivals” (Gauri et al.,

2008b). Via these, the importance of store location and its accessibility in terms of loyalty

can be seen. Retail gravitation theory refers to the trade-off between the distance to a store

and its attractiveness: busy or time limited consumers might choose an alternative stores or

brands located nearer their houses instead of remaining loyal to specific brands or stores

located further away. Consumers always seek the optimal choice which is beneficial to them

(Jacoby et al., 1976).

Store loyalty can be defined as “the intention and readiness to repurchase at a particular

store or recommend a store” (Swoboda et al., 2013:252; Oliver, 1999; Evanschitzky and

Wunderlich, 2006). As explained above, before deciding where to buy products, customers

tend to compare many retailers, and if the competitive level is high and rivals are located near

focal retailers, customers will have more choices and have a tendency to be less loyal to the

focal retailer, thus the competitive advantage of firms can be eroded (Seiders et al, 2005)

Erbiyik et al. (2012:1046) summarised some of the previous studies around retail store

site location and presented some criteria they believed firms consider before establishing new

stores (Table 2.5.7; 2.5.8). Finally, Erbiyik et al. (2012) proposed 5 groups, including costs,

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competition conditions, traffic density, physical features and location of stores which they

tested with samples in Turkey.

Table 2.5.6: Retail site store location selection main criteria comparison martrix

(Erbiyik et al., 2012:1410)

Table 2.5.7: Comparison matrix of sub criteria for store location main criteria

(Erbiyik et al., 2012:1411)

Based on the findings of Erbiyik et al. (2012:1410), “traffic density” and “competition

conditions” are the most important factors that retailers prioritise and consider before setting

a new store. Retail stores are often located on the main street and in the shopping centre.

Retailers might need to strike a balance between firms’ advantages and stores’ location in

order to attract more customers.

According to Swoboda et al., (2013:253), “the retail brand of a chain store retailer acts as

an umbrella that comprises each individual store”, each store has different characteristics and

advantages even if they are homogeneous in terms of decoration, products and managerial

style. In this research, Swoboda et al., (2013) found a strong relationship between store

accessibility and customer loyalty. In addition, they also emphasised that “a high level of

competitive intensity significantly decreases the effect of store accessibility on store loyalty”

(Swoboda et al., 2013:258). In other words, “the store accessibility of the focal retailer is less

important for securing consumer loyalty if there are more shopping alternatives in an area”

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and “when the distance to the next shopping alternative for a specific product is greater, store

accessibility is more important” (Swoboda et al., 2013:258). In current literature, there seems

to be a lack of studies looking at whether there is a positive relationship between store

accessibility and loyalty. Therefore, this relationship is going to be proposed at 2.5.13.2 and

investigated in this thesis (Chapter 6).

2.5.8.3. Customer service

Over the past two decades, literature in marketing has explored the importance of

customer service as well as its effect on customer satisfaction and customer loyalty (Berman

and Evans, 2010; Levy and Weitz, 2007; Innis and La Londe, 1994). Providing excellent

customer service is the best way to distinguish a firm from its rivals (Lovelock, 2001;

Kanovska, 2009) and can be considered as a firms’ strategic weapon (Abu-ELSamen et al.,

2011). Many empirical studies have found that if customers are treated well, they have a

tendency to perceive positively anything offered by the service provider, reducing their

complaints and being more loyal, behaving cooperatively and being willing to pay higher

prices (Woods, 1999; Akroush et al., 2005; Stamatis, 1996).

Customer service is defined as all activities delivered by retailers, which can improve

customer perceived value during the shopping process (Levy and Weitz, 2007; Lusch et al.,

2011). It includes tangible or intangible values that firms provide consumers in an indirect or

direct way (Kursunluoglu, 2011). To create long-term customer satisfaction, it is not enough

to offer high quality products , customer services such as home delivery, sales and after-sale

services, information desk provision, payment facilitation, free car parks, clean restrooms,

and customer complaint points are all required (Kursunluoglu, 2014). Excellent customer

service is significantly positively associated with consumer spending (American Express

global customer service barometer, 2011), customer satisfaction and loyalty as well as

positive words-of-mouth (Zeithaml, 2000; Durvasula et al., 2005). Poor customer service is

directly related to increased customer switching and dissatisfaction (Bitner et al., 2000;

Rightnow Technologies Inc., 2010). Employees have a vital role in delivering services.

Lounsbury et al. (2012:518), Occupational Information Network (2012) reported many

attributes that employees need to own in order to deliver excellent customer services, which

are “attention to detail, integrity, dependability; stress tolerance, self-control; social

orientation and concern for others”. Staff needs to be more friendly, empathetic and attentive

(Baydoun et al., 2011). Frei and McDaniel (1998), Mount et al. (1998), Hu and Jasper (2006);

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Hu (2011), Hurley (1998) found a strongly positive relationship between customer service

quality and employees’ personalities, the Big Five Model of personality includes “Openness,

conscientiousness, extraversion, agreeableness, emotional stability”. Gundala (2010)

confirmed that consumers will return to stores as they find sales personnel who are friendly,

supportive, courteous and attentive during clothing shopping processes. It also helps the store

improve their store image.

Kursunluoglu (2014) has found eight main variables of customer service in his

comprehensive research (see Figure 2.5.12) which are classified as follow: “Basic customer

service” such as having accurate price tags, short waiting time during the consumer check-out

process, clean restrooms offered, easy product return policy, quickly solved customer

complaints, good ventilation systems, free offered vehicles such as wheelchairs and

escalators for disabled consumers, well-organised shopping centres; “Incentive customer

service” such as notice boards, lost property units, free call centres, guarantee and repair

services, customer information units, free buses offered for customers to reach shopping

centres, free home delivery services for high spenders; “Facilitative customer service” such

as free car parks, rest areas for customers, ATM machines; “Customer service about

payment” that facilitate consumers during their payment, retailers need to accept a variety of

payment methods; “Customer service about atmosphere” which deliver nice music, provide

some quiet and luxury shopping atmosphere; “Customer services in Encounter Stage” that

offer free gift wrap services, genial employees who can give all the information customers

may request; “Informative customer service” refers to how in-store advice to customers on

how products should be used, the provision of informative websites and good marketing

brochures.

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Figure 2.5.12: The customer service factors (Kursunluoglu, 2014:535, 536)

Kursunluoglu (2014:538) found “customer service had effects on customer satisfaction”

and “customer service could explain 13.9 percent of total variance in customer satisfaction

and 12.5 percent of total variance in customer loyalty” as exploring the above presented eight

factors about customer service in the shopping centre. In addition, Kursunluoglu

(2014:539,549) also stated that “comparing with other antecedents of satisfaction and loyalty,

customer service effects are not so powerful”. As looking at how these single factors affect

customer satisfaction and loyalty, Kursunluoglu (2014:541) concluded that “CSA, ICS, CSE,

CSP have effects on satisfaction and loyalty, whereas BCS, FCS, CSC, InCS do not affect

satisfaction and loyalty” (see Figure 2.5.12) and there are three variables only affecting

loyalty: incentive customer services, customer services in the encounter stage, and customer

services surrounding payment. And Mangnale and Chavan (2012) indicated that customer

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service has a positive impact on customer perceived value. There has been an ongoing debate

among researchers on the topic of the relationship between customer service and other

constructs. In this research, the question of whether customer service positively affects

customer perceived value will be examined. The hypotheses will be proposed at section

2.5.13.2.

2.5.8.4. E-service quality

E-service quality is a part of service quality. In recent years, the internet has become a

vital channel for selling most goods and services (Teo, 2006; Zeithaml et al., 2002). “The

internet provides a marketplace where buyers and sellers conduct transactions directly,

interactively” (Yun and Good, 2007:4). The theoretical background of e-service quality has

been created based on the approach of Zeithaml et al. (2000, 2002). These scholars suggested

the framework named e-SERVQUAL. The research on e-service quality has been conducted

by many researchers (Brady and Cronin, 2011; Collier and Bienstock, 2006; Fassnacht and

Koese (2006), Rowley (2006). Figure 2.4.13 presents the historical development of service

quality scales in online retail (Kalia, 2017:631). In the research of Zemblyte (2015), he

proposed the research framework based on previous studies with 14 dimensions forming in

three scales (see Figure 2.5.14) but the results do not support the suggested three scales

(Figure 2.5.14), he concluded that “e-service quality from the customers’ perspective is a

four-dimensional construct, i.e. composed of four dimensions: compensation, responsiveness

and fulfillment, website operation, and reliability” (Zemblyte, 2015:806). And the most

important dimension is the compensation which explained 41.89% of e-service quality,

followed by responsiveness and fulfillment (20.17%), website operation (5.41%) and

reliability (3.69%).

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Figure 2.5.13: Historical development of service quality scale in online retail

(Kalia, 2017:631)

Figure 2.5.14: The conceptual framework of e-service quality (Zemblyte, 2015:803)

The research from Yun and Good (2007), showed that e-service can improve e-tail store

image (online retail store image), affect customer perceived value and customer loyalty.

Ribbink et al. (2004:446) found “the e-service quality dimension of assurance, i.e. trusting

the merchant, influence loyalty via e-trust and e-satisfaction. Other e-quality dimensions,

such as ease of use, e-scape, responsiveness and customisation influence e-loyalty mainly

indirectly, via satisfaction”. In the online environment, e-satisfaction, which largely explains

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the variance in e-service quality, has positive and direct impact on e-loyalty, e-trust is also

used to explained e-loyalty but it is not a major contributor to loyalty (see Figure 2.5.15).

However, the study from Chang and Wang (2011:346) showed that e-service quality did not

directly significantly affect customer loyalty, but “it does so indirectly through the mediation

of perceived value and satisfaction” and in an online shopping environment, e-service quality

has a significant positive effect on customer perceived value.

Figure 2.5.15: Empirically validated model: coefficients (t-values)

(Ribbink et al., 2004:453)

The current studies found contradictory findings about the role of e-service quality to

customer perceived value and customer loyalty. Therefore, whether postitive relationships

between e-service quality and customer perceived value/customer loyalty exist will be

investigated in this research and hypotheses are going to be proposed for testing in 2.5.13.2.

2.5.8.5. Loyalty programmes and promotion effects

Loyalty programmes have recently gained a considerable practical and academic

attention in the context of customer retention. As retailers found it difficult to differentiate

them from others, they usually develop customer loyalty programmes through which they can

create switching costs to deter their customers from changing to other providers (Ho et al.,

2009; Gable et al., 2006), obtain a win-win situation with their customers and realise long-

term economic benefits (Palmer et al., 2000; Rapp and Decker, 2003; Stauss et al., 2001;

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Bolton et al., 2000; Verhoef, 2003; Yi and Yeon, 2003; Noordhoff et al., 2004, Gustafsson et

al., 2004). These benefits can be monetary or non-monetary incentives such as rebates,

bonuses or services (Mulhern and Duffy, 2004). Lin and Bennett (2014:933) defined loyalty

programmes as “an organised marketing activity that offers a firm’s customers additional

incentives, rewards or benefits to entice them to be more loyal”. The loyalty programmes also

“allow retailers to develop new ways of measuring and managing their business and their

customers’ experiences” (Dunne and Lusch, 2004:392; Levy and Weitz, 2004:341; Gable et

al., 2006:36; Gable et al., 2008)

There has been a limited number of studies exploring the relationship between loyalty

programmes and customer loyalty On the one hand, Walsh et al., (2008); Ho et al. (2009),

Noordhoff et al. (2004), Gustafsson et al. (2004), Bowen and McCan (2015), Roehm et al.

(2002), Halberg (2004), Verhoef (2003), Lewis (2004), Bolton et al. (2000) found a

positively strong relationship between the loyalty programmes offered and customer loyalty.

On the other hand, other studies showed an inconsistent or even contradictory result, in the

study of Stauss et al. (2005) also indicated that loyalty programmes can frustrate their

customers and decrease the level of customer retention (see Figure 2.5.16). Four categories of

incidents, including inaccessibility, worthlessness, qualification barrier and redemption costs

might frustrate customers. Hansen (2000:429) proved that “customer-value-oriented

differentiation in loyalty programmes may be perceived by customers as discriminatory and

unfair”. Gustafsson et al. (2004) also found “some operational problems in collecting

promised incentives for loyal behaviour and complicated operational procedures of a telecom

company’s customer club are perceived negatively by customers” (Stauss et al., 2005:231).

The research from Lacey and Morgan (2008:9) showed that “no evidence is found in support

of H2b for how membership in loyalty programmes increases customers’ willingness to share

information”, “no evidence for H4b is found to demonstrate that loyalty programme

membership positively impacts the relationship between committed customers and their

willingness to engage in word-of-mouth referrals” and “no evidence is found in support of

H5b that loyalty programme membership positively magnifies the influence of the relationship

between commitment and increased repatronage intentions”. The study from Lin and Bennett

(2014) showed the hypothesis that loyalty programme membership positively moderates the

relationship between customer experience and customer satisfaction to be rejected. However,

the findings from Chen and Wang (2009) showed that loyalty points can be considered as a

switching barrier and hold a moderating effect playing a vital role in customer loyalty. The

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previous findings continue to be debated among scholars. Therefore, the relationship between

loyalty programs and customer loyalty should be investigated in this research.

Figure 2.5.16: General frustration model (Stauss et al., 2005:236)

Promotion can be considered as an effort to increase sales in the short-term (Bawa and

Shoemaker, 1987; Smith and Sinha, 2000). Previous studies investigated the link between

sales promotion effects and switching barriers as well as their influence on customer loyalty.

The study from Tung et al. (2011) found that promotion effects have a significant positive

impact on loyalty. This result is consistent with previous findings from Thaler (1985),

Zeithaml (1988), Grewal et al. (1998). And the research of Kim (2019) suggested that

customers’ perceived (un)fairness could be affected by the selection of price promotion.

Therefore, whether there are postive relationships between promotion effects and customer

loyalty/customer perceived value will be investigated in this research. The hypotheses will be

proposed in 2.5.13.2.

2.5.8.6. Product quality and price

Empirical studies have paid considerable attention in researching factors affecting

customer satisfaction, they found that a products’ quality (Hansen, 2003; Huddleston et al.,

2009), service quality (Jayawardhena and Farrell, 2011; Nesset et al., 2011) and the product

assortment (Pan and Zinkhan, 2006; Hoch et al., 1999) are definitely good indicators. It can

be noted that product quality has both subjective and objective dimensions. The subjective

aspect refers to the quality of products perceived by customers (Anselmsson et al., 2007), in

which customers could make a judgment about product quality based one product-associated

attributes (Zeithaml, 1988) but actually it might be impossible to make accurate judgment

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about the quality of ingredients and components included inside products (objective

dimension). Therefore, all judgments about product quality based on customers’ viewpoints

are regarded as subjective. In the process of evaluating food quality, customers can perceive

taste, quality of ingredients, nutritional information, freshness, naturalness, appearance or

even the odour of products (Anselmsson et al., 2007; Grunert, 2005). Lloyd and Luk (2010)

listed price, service quality and product quality as the top three drivers of customer perceived

value. Jiang et al. (2018) endorsed that product quality and price have a positive impact on

customer perceived value with beta value of 0.210 and 0.120 respectively. Eid (2015), Eid

and El-Gohary (2015), El-Adly’s research (2018) shows that price has a significant direct

positive effect on customer satisfaction (0.140) and customer loyalty (0.088 with p-value

<0.05). In accordance with previous studies, the hypotheses about the positive relationships

between price/ product quality and customer perceived value, customer satisfaction and

customer loyalty will be proposed in section 2.5.13.2.

2.5.9. Corporate social responsibility, corporate image and customer loyalty

Corporate social responsibility (CSR) activities are considered as “long-term

investments” and are a tool in ensuring firms’ long-term sustainable development (Gurlek et

al., 2017:409). They can help firms attract the attention of customers via their activities. The

research of Marin et al. (2009) and Martinez et al. (2014) demonstrated that customers pay

more attention to firms who engage positively with social and environmental issues.

Although CSR is a popular topic in literature, scholars have not agreed a comprehensively

accepted definition of CSR (Mackenzie and Peters, 2014). Garay and Font (2012) define CSR

as “the voluntary contribution of companies to environmental, economic and social

development”, Nicolau (2008) defines it as “a company’s obligation to be accountable to all

of its stakeholders affected by its operations and activities” (Gurlek et al., 2017:411). Or CSR

refers to all ethical and responsible manner of firms toward its stakeholders around firms’

external and internal environment (Aktan and Boru, 2007; Park et al., 2014).

Corporate image can be defined as the overall impression of consumers on the physical

and behavioural attributes of the company (Barich and Kotler, 1991; Nguyen and Leblanc,

2001; Rehman, 2012). Or Keller (1993) defined that corporate image is “the perception of an

organisation held in the consumer memory, which works as a filter influencing the perception

of the company” (Calvo-Porral and Levy-Mangin, 2015:127). It stems from all of the

customer experiences (Lai et al., 2009) and their perceptions. It can be seen that corporate

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social responsibility might affect corporate image. Some previous empirical studies found

that corporate image has no direct effect on customer loyalty (Aydin and Ozer, 2005; Lai et

al., 2009) but corporate image can enhance customer satisfaction (Lai et al., 2009; Chang and

Yeh, 2017). However, the studies from Ball et al. (2006), Nguyen and Leblanc (2001),

Flavian et al. (2005) showed that corporate image is related to the customer retention

likelihood and customer loyalty; Calvo-Porral and Levy-Mangin (2015) found that customer

satisfaction is significantly affected by corporate image (see Figure 2.5.17)

Figure 2.5.17: Final causal relationships for virtual mobile service

(Calvo-Porral and Levy-Mangin, 2015:134)

According to Salmones et al. (2009) and Perez and Bosque (2015:5) “loyalty behaviour

is one of the most representative ways in which customer express their satisfaction with

corporate performance, and it is closely linked to the profitability of companies” (Figure

2.4.26). Many researchers have explored the relationship between CSR and loyalty

behaviour, but the results of all previous studies generate controversy when empirical

evidence keeps showing many contradictory findings. On the one hand, Perez et al. (2013),

Mandhachitara and Poolthong (2011), Leaniz and Rodriguez (2015), Ofluoglu and Atilgan

(2014), Liu et al. (2014) found that there is a positive relationship between CSR image and

customer loyalty. Perez and Bosque (2015) found that the CSR image included CSR society,

CSR customers, CSR employees affect customer loyalty via customer satisfaction (see Figure

2.4.26). Specifically, “customer perception about the CSR oriented to customers also

significantly and positively impacted customer satisfaction, but, again, the perceptions of

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CSR oriented to employees did not significantly affect this affective variable” and the CSR

oriented to the society do not have a strong effect on customer satisfaction (Perez and

Bosque, 2015:21,22). However, Rashid et al. (2014) claimed that CSR activities based on the

environment may positively affect customer loyalty. In addition, Gurlek et al. (2017), while

exploring the case of five star hotels in Istanbul, have also indicated that CSR creates

customer loyalty partially through corporate image (Figure 2.5.18).

Figure 2.5.18: Structural model estimation in the hotel sample (Gurlek et al., 2017:419)

On the other hand, Carrian and Attalla’s studies (2001), Salmones et al. (2005), Chang

and Yeh (2017) could not find evidence of the above relationship. Chang and Yeh’s results

(2017) found that there is no direct effect between CSR and customer satisfaction as well as

CSR and customer loyalty. Then, they tested between triple variables (customer satisfaction,

CSR and customer loyalty)/(corporate image, CSR and customer satisfaction), they added a

new conclusion: “without a mediator, CSR will have no direct effect on customer satisfaction

and customer loyalty in Taiwan’s intercity bus services” (Chang and Yeh, 2017:43). These

findings also coincide with the study by Kaplan et al. (2014). In accordance with previous

studies, the hypotheses will be proposed in section 2.5.13.2.

It can be noted from the outset; the researcher did not review “trust” and “habit”

in her study because there are limited studies on how trust and habit constructs related

to customer perceived value and customer loyalty. However, these two constructs were

found to have relationships with customer perceived value and customer loyalty based

on consumer interviews (Chapter 4). Again, it can been seen how powerful and

beneficial the use of a mixed-method brings to the research and interviewing consumers

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in the specific market (Vietnam) can justify and fill the gaps between the future

proposed research framework which is built based on literature review and the real

situation of Vietnamese supermarket consumers’ perception connected to customer

lotalty. Therefore, they will be added to the original proposed research framework and

it will be reviewed as follows:

2.5.10. Trust

Yaqub et al. (2010) stated the crucial role of trust in firms’ success or failure. Many

researchers viewed “trust as a perceived confidence benefit, which reduces anxiety and

increases comfort as a result of customers knowing what to expect from a service provider”

(Henning-Thurau et al., 2002, Singh and Sirdeshmukh, 2000; El-Manstrly, 2016:146).

Sirdeshmukh et al. (2002) argued that trust generates customer perceived value via offering

rational benefits and removing all uncertainty related to a relational exchange. Guenzi et al.

(2009), Konuk (2018), Walter and Ritter (2003) and Ponte et al. (2015) found that trust

enhances customer perceived value by reducing non-monetary costs perceived, such as the

effort and time for consumers to find their appropriate providers, then affecting customer

loyalty as well. In particular, Konuk (2009) found that trust is positively related to customer

perceived value (β= 0.45, p<0.001) while Guenzi et al. (2009) found that trust in the store

can explain 32.6 percent of variation in perceived value and trust in the sales person has no

impact on perceived value. From these results, it is plausible to expect that customers with

higher trust can lead to higher perceived value; the hypothese will be proposed in section

2.5.13.2.

2.5.11. Habit

Consumer habits are defined as natural responses of people towards consumption

activities, which are affected by many factors, including their surrounding environment

(Verplanken and Aarts, 1999). Habits allow people in their own ways to use their finite

resources to make the best consumption style choices. Marketers have to consider, as they

attempt to attract more customers and serve many segments whether the consumer is resistant

to immediately changing their habits because it might cost additional resources (Wood and

Neal, 2009). In many cases, consumers might express their loyalty because of habit issues.

For instance, consumers may be “lazy” towards finding other providers, or may struggle to

change their current habits and tend to be loyal to their existent providers (Liu et al., 2015).

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The study of Liu et al. (2015) shows that habit is a strong determinant of loyalty (beta value

is 0.39). In accordance with previous studies, the hypothis will be proposed in section

2.5.13.2.

2.5.12. Customer loyalty

Customer loyalty is an ultimate goal and dream of all retailers; it could help firms

increase from 25-85 percent profit (Reichheld et al., 1990). According to Reichheld (1996),

Chang and Yeh (2017) customers tend to be loyal to firms that offer superior value compared

to their rivals, and these customers are willing to have an intensive relationship with firms

over time that can help firms save much money for their marketing campaigns as they launch

new products or offer new services. These factors can contribute to firm’s higher profit.

Therefore, customer retention can be seen as a critical factor to firms’ survival (Hoffman and

Lowitt, 2008). Customer loyalty is defined by many researchers in different ways. However,

they all have two dimensions, which are: customers repeatedly purchase a good or service;

and having favourable attitudes toward a good or service offered by companies (Kim et al.,

2004, Reynolds and Arnold, 2006; Athavale et al., 2015). Customer loyalty is defined as “a

deeply held commitment to re-buy, re-patronise a preferred product or service consistently in

the future, thereby causing repetitive same-brand or same brand-set purchasing, despite

situational influences and marketing efforts having the potential to cause switching

behaviour” (Oliver, 1997:392). Many firms compete fiercely to get more customers. It can be

seen that price is one of the factors influencing customer loyalty; however, competitive

pricing might not guarantee customer loyalty in the long-term (Scott, 2001; Schultz and

Bailey, 2000). From the beginning, Oliver (1999) classified loyalty in four steps which are

cognitive, affective, conative and action. The study from Sivadas and Baker-Prewitt

(2000:78) in a retail store setting found a strong support for the model, in that “cognitive

loyalty is a significant predictor of affective loyalty; affective loyalty is a strong predictor of

conative loyalty and conative loyalty significantly affects action loyalty”. Then, Bowen and

Chen (2001), Khan (2009), Chiu et al. (2013) have divided loyalty into two groups including

behavioural and attitudinal. Behavioural loyalty reflects customers’ action of repetitive

purchasing of products (Kandampully and Suhartanto, 2000). However, in some cases,

consumers repeatedly purchase but it cannot be seen as loyalty due to situational effects such

as low price, constant promotion programmes and proximity (Hartmann and Ibanez, 2007).

Therefore, many researchers have indicated that behavioural approach was not sufficient to

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explain customer loyalty. Attitudinal loyalty relates to customers’ psychological and

sensation orientation, they have a positive feeling about retailers and are willing to introduce

others to buy products or services from the retailers, reflect a positive word-of-mouth

communication (Kursunluoglu, 2014; Martinez and Rodriguez del Bosque, 2013). Rowley

(2005) proposed that customer loyalty should be separately classified into four groups:

“captive, convenience-seeker, contented and committed”. But the most widely accepted and

applied classification about customer loyalty is still “behavioural and attitudinal aspects”

(Han et al., 2011; Bowen and Chen, 2001)

Based on the above analysis, most retailers’ growth goals should be generating a

customer loyalty strategy and explore deeply which factors have a significant effect on

customer loyalty. Customer defection risk within the retail industry remains relatively high.

Hoffman and Lowitt (2008) found that 70 percent of US consumers demonstrated their

faithfulness to their favourite retailers, but in the case of properly enticed programmes offered

by rivals, 85 percent of these so-called loyal customers are willing to switch immediately.

As explained above, customer loyalty is affected by many factors, and any improvement

in customer loyalty will lead to increased firms’ profits (Hallowell, 1996; Aksu, 2006).

Researchers have investigated the structural linkage between customer loyalty and its

predictors. It has attracted great interest from academics and practitioners. In typical service

quality - customer satisfaction and loyalty has been explored (Orel and Kara, 2014; Storbacka

and Strandvik, 1994; Caruana, 2002; Namukasa, 2013; Chen and Hu, 2013). Service quality

has been considered as the key driver of loyalty (Lai et al., 2009). However, some researchers

have also proved that customer satisfaction is a weak indicator in terms of customer loyalty

(El-Adly and Eid, 2016; Prentice, 2014). From these studies, customers were happy and

highly satisfied with products or services offered, but they did not return and repeatedly

purchase (Prentice, 2014; Kale and Klusberger, 2007; Zeithaml et al., 1996; Reichheld and

Sasser, 1990; Barber et al., 2010). In addition, Prentice (2014) confirms that, depending on

the industry which firms are serving, service quality might not always generate customer

satisfaction and loyalty; via the research he proved that there are some dimensions of service

quality (model presented above) expressing negative effects on customers’ favourable

behaviour. Therefore, the relationship between these factors is still being debated, and there is

little homogeneity over the operationalisation of the construct of loyalty amongst researchers.

Agustin and Singh (2005) found that “relational trust and value are the strongest determinants

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of loyalty rather than satisfaction” and “service quality was also found as an antecedent of

customer loyalty (Wong and Sohal, 2003)” (Kursunluoglu, 2014:532). Kumar et al.

(2013:258) demonstrated that although there is a positive relationship between customer

satisfaction and customer loyalty, the variance explained by just satisfaction is very small

(around 8 percent), therefore, they proposed scholars should investigate customer loyalty

with many other variables such as customer perceived value, switching barriers and relational

variables such as trust, commitment, relationship age, and loyalty programme membership

(Bowen and Shoemker, 1998; Hennig-Thurau et al., 2002; Matzler et al., 2008; Lin and Lee,

2012). Other studies investigated customer loyalty and they considered service quality,

satisfaction, perceived value, price, brand image, and identity as antecedents of loyalty

(Barber et al., 2010; Kuenzel and Halliday, 2010; Ryu et al., 2012; Marinkovic et al., 2013).

In contrast, Lou and Bhattacharya (2006) and Oliver (1997), Kim et al. (2004), Shankar et al.

(2003), Chadha and Kapoor (2009), Chang and Yeh (2017) found that customer satisfaction

is a major driver of customer loyalty and it is well-known and confirmed by many

researchers.

In section 2.5, much literature has been explored to consider the relationship between

various dimensions to determine whether it affects customer loyalty. However, there remain

different findings among scholars. Therefore, the following proposed research framework

will be applied in this thesis in the context of the Vietnamese retail industry to determine

whether there is support for or against the previous differing schools of thought.

2.5.13. Research gaps, proposed research framework and hypotheses

2.5.13.1. Research gaps

The above presents all relevant literature relating to the research topic. From the

beginning, I have indicated the approaches used for searching literature and proposed four

main themes that the research should investigate; the outline of the whole literature review

part had been presented, followed by examining the four main themes (Section 2.2 to Section

2.5). At the end of these reviews, literature on Strategic Groups, Retail Industry, The

Vietnamese Retailing Industry, and Customer Loyalty has supported and clarified the

research topic. Based on this review, the research’s gaps can be listed as follows:

1. The relationship between customer satisfaction and customer loyalty, factors

influencing satisfaction, customer perceived value as well as which factors

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affecting customer loyalty are still being debated between scholars (see Chapter 2

section 2.5).

2. Most studies, which relate to customer loyalty in the retailing industry, have

separately explored customer loyalty and specific factors such as customer

satisfaction, store image, corporate image, social responsibility, switching cost,

available alternative attractiveness, and loyalty programmes. There is no research

examining how many factors simultaneously affect customer loyalty.

3. There is no comprehensive published paper investigating customer loyalty in the

supermarket sector in Vietnam as well as Vietnamese consumption style.

4. Previous research has not investigated factors affecting customer loyalty in

different strategic groups, rather they have examined specific industries and

generalised for the whole industry. Based on strategic theories in a specific

industry, different strategic groups might have different factors affecting customer

loyalty. It means that the differences between strategic groups in the same

industry have been ignored (Section 2.5 reviewed factors which relate to customer

loyalty. However, no research has been linked with strategic terms - section 2.2.

Therefore, such research is needed).

5. Differences in relationships between constructs based on income, location,

gender, age and occupation have been under-researched.

This research aims to investigate and fill the above mentioned gaps via answering five

questions as follows:


at which level?




RQ4: Are there any differences in terms of factors affecting customer loyalty between

strategic groups in the Vietnamese retail industry?



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2.5.13.2. The proposed conceptual research framework and hypotheses

In the end of each sub-section of section 2.5, the researcher has reviewed and debated

a contradictory relationship between many related dimensions among scholars. These on-

going debates reveal support for the related findings and lead to different schools of thoughts,

some scholars have supported, and others have not. In particular, there remains no consensus

in the literature on which factors affect customer loyalty.

The following path model of latent factors (Figure 2.5.19) is proposed based on

results from the literature review where contradictory findings from different groups of

researchers have been found, and the gaps which are presented above. The main reason for

creating this model is to clarify the gaps based on the literature review and provide a direction

for this study. Figure 2.5.19 is also considered as the proposed conceptual model of this

research. The procedure of creating Figure 2.5.19 is going to be presented as follows. The

initial outline of figure 2.5.19 was created based on three main themes, including constructs

named “customer perceived value”, “customer satisfaction” and “customer loyalty”. In this

research, due to objectives of the research, there were only three constructs being treated as

dependent factors. The researcher again re-checked from the available literature and

investigated factors that might directly and indirectly affect “customer perceived value”,

“customer satisfaction” and “customer loyalty”. Then, the initial research framework was

drawn. After that, the researcher continued to propose linkages/connections between factors

based on the results of the literature review of which the hypotheses are based on. After this,

the researcher built manifest variables which related to its latent factors based on the

literature review. In some cases, manifest variables used in this research are a combination

between reliable manifest variables created and used by many well reputed academic

researchers in the retail field. In order to make sure that all relevant items (constructs) were

included, the researcher re-checked both the latent constructs and manifest variables related

to customer perceived value, customer satisfaction and customer loyalty. There are some

other factors mentioned in other research, such as how reputation affects customer loyalty;

but it was not investigated in the review because the manifest variables which are used to

measure “reputation” construct are also used to measure “corporate social

responsibility/brand retail experience/store image”. As a result, the researcher examined

thoroughly to make sure that all necessary manifest variables were included. In later research,

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if these variables load the same content to explain latent variables, they will be removed

automatically during the process of exploratory factor analysis (EFA).

It can be noted again from the outset, the researcher did not review “trust” and “habit”

in her study. However, these two constructs were found to have relationships with customer

perceived value and customer loyalty based on consumer interviews (Chapter 4). Therefore,

they have been added to the original proposed research framework, and “trust” and “habit”

constructs are shown in a bold red colour in this framework. Control variables including

income, location, age, gender and strategic groups will be input into the model during

hypothesis testing in order to investigate whether these variables affect the three main

dependent variables (customer perceived value, customer satisfaction and customer loyalty;

hypothesis 1 to hypothesis 5).

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+ H6

+H14

+H12A

+H7B +H16 +H25

+H26 +H18 +H15

+H11B

-H10B

+H11A

+H9B

H6

+ H7A

+H8

+H

22

B

+H23

Figure 2.5.19: The proposed conceptual model of this research

Instore

logistics

ssss

E-service

quality

Service

quality

Customer

service

Customer

experience

Retail brand

experience

Product

quality Price

Corporate social

responsibility

Store

image

Habit

Trust

Switching

costs

Alternative

attractivenes

s

Loyalty

programs

Promotion

effects

CUSTOMER

PERCEIVED VALUE

Store

accessibility

CUSTOMER

LOYALTY

Gender Age Location

s

Income Strategic groups

CUSTOMER

SATISFACTION

Corporate

image

Constructs added from the

findings of Phase Two:

TRUST and HABIT Control variables

7 items 6 items 10 items 3 items 6 items 3 items

3 items

6 items

4 items

4 items

6 items 3 items 3 items

4 items 10 items

6 items

4 items

7

ite

ms

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All hypotheses of this reseach are presented in Appendix 2.1 and Appendix 2.2 to

demonstrate a link between hypotheses and research questions which can be briefly presented

here:

Research questions Hypotheses

RQ1: What factors directly affect customer

loyalty in the Vietnamese supermarket and at

which level?

Customer loyalty: H1C, H2C, H3C, H4C, H5C

H7B, H8, H9C, H10B, H12C, H15, H17C,

H17D, H18, H19B, H20C, H21C, H22B, H26

RQ2: Is customer satisfaction a major

indicator for customer loyalty or not?

H8


perceived value, customer satisfaction in the

Vietnamese supermarket and at which level?

Customer perceived value: H1A, H2A, H3A,

H4A, H5A, H9A, H12A, H13A, H16, H17A,

H17B, H19A, H20A, H21A, H22A, H25

Customer satisfaction: H1B, H2B, H3B, H4B,

H5B, H6, H7A, H9B, H10A, H12B, H13B, H14,

H20B, H21B, H24

RQ4: Are there any differences in terms of

factors affecting customer loyalty between

strategic groups in the Vietnamese retail

industry?

Multigroup analysis

RQ5: Are there differences between the

factors affecting customer loyalty in the retail

industry based on income, gender, location,

age groups, occupation and education levels?

Multigroup analysis

All control varibles will be tested as to whether they affect customer perceived value

(H1A, H2A, H3A, H4A, H5A), customer satisfaction (H1B, H2B, H3B, H4B, H5B) and

customer loyalty (H1C, H2C, H3C, H4C, H5C) or not. Appendix 2.3 sumarises the latent

factors and manifest variables used in this research.

With the above research framework and based on research objectives presented at

chapter 1, the researcher is going to conduct many qualitative and quantitative steps based on

Cannon (2004), who proposed steps in the process of conducting a mixed method, in order to

achieve the research’s objectives:

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Step 1: Conducting experts’ inteviewing in order to divide supermarkets into their right

groups.

Step 2: Conducting supermarket-consumer interviewing in order to justify the

proposed research framework and investigate whether other factors, which have not

been investigated in the literature part, should be considered in the Vietnamese grocery

market.

Step 3: Using EFA (exploratory factor analysis) technique for all manifest variables to

examine its consistency and what variables should be remained or eliminated from the

data set.

Step 4: Revising the model

Step 5: Test CFA (confirmatory factor analysis) and SEM (structural equation

modeling) to investigate the research questions and achieve the research’s ojectives.

Besides that, multigroup comparisons across groups (which is considered as advanced

SEM exploration) for factors relating to customer satisfaction, customer perceived value and

customer loyalty will be investigated at chapter 6.

2.5.14. Summary

This part is considered as a main theme of the review. It explores many factors related

to and possibly affecting customer loyalty. From the beginning of this section, the researcher

presented a literature review on consumers’ preferences, consumer behaviour, customer

experience, customer perceived value and customer satisfaction; followed by perceived

switching cost and switching barriers, brand experience and service quality. The section had

also covered corporate factors which might indirectly influence the main theme of “customer

loyalty” such as in-store logistics, store image, store accessibility, customer service, e-service

quality and product quality. Then, corporate social responsibility, trust and habit were also

investigated. Finally, some basic reviews around customer loyalty and the debate between

scholars about factors affecting customer loyalty was presented, followed by indications of

the research gaps; discussion of the proposed research framework and hypothesis of this

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research. The next chapter is going to present how the research will be conducted (Chapter 3:

research methodology).

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Chapter 3: Research Methodology

3.1. Introduction

Previous chapters can be regarded as a secondary data source in order to present much

background information relating to customer loyalty, different strategic groups, the retail

industry and the Vietnamese retail industry. This chapter is going to present the research

methodology applied, the researcher will first restate research objectives and research

questions, highlight differences between philosophical stances and paradigms, then indicate

the applied philosophy and paradigm for this research. This will be followed by the research

process and research methodology.

3.2. Research objectives and research questions restated

The research objectives are as follows:

Providing insights about the Vietnamese retailing industry, classify all current

supermarket firms in Vietnam into their correct strategic groups.

Investigating factors directly affecting customer loyalty, customer satisfaction and

customer perceived value in Vietnamese supermarkets by simultaneously researching

and comparing different strategic groups.

Examining whether there are differences between factors affecting customer loyalty

based on age groups, location, income, gender, occupation and education levels.

There are five research questions proposed in this study:


at what level?






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3.3. Research philosophy and research paradigms

3.3.1. Research philosophy and research paradigms

Before examining the research paradigm, it is crucial to absorb knowledge about all

assumptions demonstrated in the research philosophy. These assumptions relate to how

knowledge is developed and analysed as well as its impacts on future applied research

methodology (Sauders et al., 2007; Guba, 1990; Chua, 1986). This part will shed light on

three philosophical stances which underpin the research paradigm: ontology, epistemology

and methodology (Guba and Lincoln, 2005; Bryman and Bell, 2011). Ontology is concerned

with the nature of reality. From this viewpoint, the reason of the existence can be drawn

(Chua, 1986), which answer how the world looks (Solem, 2003; Bryman and Bell, 2007), and

“whether the social world is external to social actors or the social actors fashion it” (Sobh and

Perry, 2006:1200). Epistemology refers to the nature of knowledge and how the knowledge

can be obtained. As Saunders et al. (2007: 102) stated epistemology deal with “what

constitutes acceptable knowledge in the field of study”, and “in the discipline” (Bryman and

Bell, 2011:15). In fact, it is all based on the theory of knowledge, “grounds of knowledge”

(Burrell and Morgan, 1979:1), demonstrating how a researcher views the world, and which

knowledge is valid and accepted. Therefore, epistemology indicated the natural relationship

between the knower (researchers) and the known (the research topic) to some extent (Guba,

1990:18). Methodology is related to the question of how the knowledge is obtained.

According to Guba (1990), this philosophical assumption will definitely facilitate researchers

(the inquirer, the knower) in finding a way of obtaining knowledge. There are relationships

between these philosophical stances. The epistemological viewpoints have been impacted by

ontological choices (Sarantakos, 2005; Collis and Hussey, 2009) and the choice of research

methodology has been traced back from these two stances (Burrell and Morgan, 1979).

There are two aspects of ontology being considered: objectivism and subjectivism

(Saunders et al., 2009). Objectivism believes that there is an independent relationship

between social actors and social entities which are already in existence. On the other hand,

subjectivism supports the view that “social phenomena are created from the perceptions and

consequent actions of social actors” (Saunders et al., 2009:111; Holden and Lynch, 2004).

Saunders et al. (2012) indicated that subjectivism concerns reality as a socially constructed

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factor in the social context; based on this viewpoint, researchers seem to concentrate more on

interpreting participants’opinions in specific situations in order to claim new arguments and

knowledge.

The two main epistemological stances are positivism and interpretivism (Collis and

Hessey, 2009). Positivist researchers conduct their study based on a value-free approach and

dichotomous thinking, all obtained knowledge should be observable and measurable,

researchers become an objective existence; they often ignore their own feelings or

interaction-involved during the research process, large samples are used to test the theory by

drawing hypothesis and conducting the research via quantitative methods to generate

objective results with high levels of crediblity and reliability (Holden and Lynch, 2004,

Easterby-Smith et al. 2012). It examines the relationship between variables (independent and

dependent ones). In contrast, interpretivists argued in different ways which indicate the action

of relying on data and number results being conducted by positivists is not enough (Näslund,

2002). Therefore, social interactions should be taken into account. Their actions aim to

develop new theories to some extent by applying qualitative research with small samples

(Meredith, 1988). Under this epistemological standpoint, the interrelationship between

researchers and what is being researched is impossible to separate during the research process

(Mangan et al. (2004). The findings can reach “a causal explanation of its cause and effects”

(Maxwell, 2005:88). The result can be less reliable compared to quantitative method, but it is

still considered highly valid as its degree of generalisation is high (Collis and Hussey, 2009).

The following table can demonstrate the differences between these two epistemological

paradigms and the main characteristics of these two methodologies:

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Table 3.1: Comparison of positivism and interpretivism paradigms

There are two methodologies being used in the research, including quantitative and

qualitative. As mentioned, the methodology can be characterised by the chosen paradigmatic

philosophy and research can be conducted in deductive or inductive ways. Deductive

approach is usually associated with positivism and quantitative research, while inductive is

suitable for interpretivism and qualitative research (Saunder et al., 2009). The deductive

approach related to “testing a theory” via theoretical hypotheses which can be developed

through literature review, from which many variables have been constructed. This method

usually applies to surveys and questionnaires (Collis and Hussey, 2003). On the other hand,

the inductive approach deals with the context and “building and generating theories”

(Bryman, 2012). Via this method, many viewpoints around the topic can be revealed and it is

not easy to turn the research findings into specific theory. Therefore, researchers often use

this technique within a limited setting and context. Empirical measurement is regarded as the

main methodology in a scientific method (Orlikowski and Baroudi, 1991). In many cases,

researchers have managed to integrate the two approaches in the research process (Lee, 1991;

Morgan, 2007; Bryman, 2012).

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Table 3.2: Comparison of quantitative and qualitative methodologies

Figure 3.1: Different logics used in quantitative and qualitative studies

Besides that, according to Saunders et al. (2008), there are two more philosophies which

are realism and pragmatism might need to be considered. The view of pragmatism posited

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that “study what interests you and is of value to you” (Tashakkori and Teddlie, 1998:30),

whereas realism refers that objects are supposed to exist independently to the human mind

(Saunders et al., 2009).

3.3.2. Apply paradigms to the thesis research

Based on the research topic previously stated, the aim of the research will be

demonstrated as follows: firstly, the research will provide insights into the Vietnamese

retailing industry, classifying all current supermarket firms in Vietnam to their right strategic

groups. Secondly, this thesis is going to investigate factors affecting customer loyalty in the

Vietnamese supermarket sector by simultaneously researching and comparing different

strategic groups. Thirdly, the research is going to examine whether there are differences

between factors affecting customer loyalty based on age groups, location, income, gender,

occupation and education levels.

It can be noted that there is no right or wrong paradigm, the chosen paradigm entirely

depends on the researcher but they must be aware of the paradigm being affected by the

nature of conducting research, philosophical standpoints as well as the research purposes

(Mackenzie and Knipe, 2006). In this thesis, the research topic related to strategy, marketing

and in-store logistics management areas which follow the scientific method and this area was

posited as belonging mostly to the positivist paradigm (Mentzer and Flint, 1997; Aastrup and

Halldorsson, 2008; Grant, 2003;). However, based on the indicated research objectives, some

of them are exploratory in nature, strategic group mapping, and consumer preferences.

Therefore, the thesis will employ a combination of ontological stances which are objectivism

and subjectivism, in appropriate ways. In other words, objectivism is a dominant stance; the

results from quantitative data collection will clearly answer the research questions. The

research follows the epistemological standpoints of both positivism and interpretivism but the

dominant stance applied is positivism. As a result, the research will use both quantitative and

qualitative research methods to answer research questions. Bazely (2003), Burke and

Onwuegbuzie (2005) indicate that this method is the use of mixed data, including both text

and numerical and using alternative tools (analysis and statistics). In that, researchers might

apply a qualitative method in one phase and use a quantitative method in another phase

during the research period, and data are integrated and mixed (Creswell et al., 2004).

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Table 3.3: Distinction between Quantitative and Qualitative Data

(Saunders et al., 2012)

Objective methods, positivism epistemology and quantitative research will be applied

dominantly, with surveys and questionnaires to obtain credible data. Researchers can observe

an independent phenomenon and generalise the results which could help to reduce the gap

between management theory and practice (Forza, 2002); its advantages are all variables being

calculated and measured comprehensively using mathematical tools and software, but it

reveals disadvantages in which if new variables are added, the relationship between

independent variables and predictors could be changed (Hair et al., 2011). On the other hand,

subjective standpoint, interpretivism and qualitative methods reveal its drawbacks in social

phenomena and its inabilities in generalising to the wider population and complex cases

(Smith 1981). However, overcoming the limitation of positivism via generating, connecting

and confirming many holistic variables for the final regression of quantitative methods if

needed could be considered as interpretivism stance’s advantages, it is mostly in the form of

words and non-standardised data but using conceptualisations for detailed analysing can be

beneficial to some extent. For these reasons and based on the nature of the research

objectives, the combination of objective and subjective, positivism and interpretivism,

quantitative and qualitative research is the best choice for this research. But the dominant

stance will be objectivism and positivism.

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3.4. Ethical theories

3.4.1. Philosophy and normative ethical theories

In the research process, researchers might need to consider ethical issues (Šmajs et al.,

2012). In a general sense, the term ethics is derived from the Greek word “ethos” which deals

with an individual’s fundamental views toward life (Sroka and Lorinczy, 2015). It refers to “a

set of moral norms, principles or values that guide peoples’ behaviour” (Sherwin, 1983;

Brunk, 2010:255), the moral principle that “individuals inject into their decision processes”

(Salehi et al., 2012:3). In the business research perspective, ethical issues relate to the

question of how researchers characterise and clarify their research topics, design their

research, and the ways in which they approach, collect, process and save data; how they

analyse and write up data collected in a moral way (Saunders et al., 2009, Cooper and

Schindler, 2008). However, “moral sentiments can be either neutral, or negatively/positively

valenced”. It means that the terms “ethical” or “unethical” demonstrate an individual’s

subjective moral judgment of which one is considered as right or wrong and good or bad

things (Brunk, 2010:255).

From philosophical perspectives, there are two fundamental normative ethical principles,

including “deontology” and “teleology” (Shanahan and Hyman, 2003). Deontology posits: “a

good will is good not because of what its effects or accomplishes, nor because of its fitness to

attain some proposed end: it is good only through its willing”, good in itself. The most

important rule in the deontological principle is: people evaluate the action as right or wrong

because of its truly right characteristics judged by higher social moral duties, norm or the

law, not because the better outcome of an action is expected (Barnett et al., 2005). On the

other hand, teleology refers to the consequences of an action, “the greatest good for the

greatest number”. Those who have supported this standpoint indicated that if stealing can

lead to a good outcome and maximises pleasure for all people in a community, it is definitely

considered as a right action and worthy of support (Sekaran, 2003).

“Kantian ethics” are considered an ethical paradigm which represents the deontological

standpoint. Kant (1979c:67) quoted: “always regard every man as an end in himself, and

never use him merely as a means to your ends”. It means that each person has their own

personal life and their purposes for living, treating them as an object to be exploited for our

purposes is considered as totally wrong (Reynolds and Bowie, 2004). This stance prefers the

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character of an action itself to the consequences of an action. Kant (1979) noted that lying is

wrong, even if it could be qualified to some extent as telling lies to friends about how good

their haircut is for a complimentary purpose (Forsyth, 1992). The Kantian ethics approach

has been applied by many researchers in business research (Petkus and Woodruff’s, 1992;

Rust et al, 2000; Ohreen and Petry, 2012; Vitell et al., 2001; Perrini et al., 2006; Mohr et al.,

2001). It has revealed a significant impact on both academic perspectives and business

practice. Kantian ethics were developed after social contract theory -“contractarian ethics”-

which considered that a person’s moral and/or political obligation has been dependant on a

contract or agreement among them to the form of the society in which they live (Skinner,

1996; Stomp, 2008; Locke, Rousseu, 1762).

“Utilitarianism” posited its contrary viewpoints compared to “Kantian ethics”, this

stance was developed based on teleology. As noted by Mill (1963-1991) “the life of a

dissatisfied Socrates is better than the life of a happy fool”, meaning that it will be better to

be a human dissatisfied than a pig satisfied. There are two different viewpoints about

happiness and the consequence of an action in this stance. Bentham supposed that the quality

of pleasure is equal, but Mill’s argument is that “simple pleasures” seem to be preferred by

individuals who have no experience with high art and they are not in a proper position to

judge if needed. Based on this, Mill proposed that extra voting power should be granted to

university graduates on the grounds that they were in a better position for judging what would

be best for society. As demonstrated above, “the greatest-happiness principle” has been

applied in this perspective, the outcome of an action should be taken into account in partly

considering the character of an action (Shanahan and Hyman, 2003).

Beside the two main ethical paradigms above, “virtue ethics” (charactered-based ethics)

should be considered. This stance is centred around the idea of individual character rather

than result-based ethics (utilitarianism) or the character of an action (Kantian ethics). It

means that virtue ethics is person-based rather than action-based. This standpoint deals with

the rightness or wrongness of individuals’ action as well as providing a guidance that

demonstrates which characteristics and behaviour of a good person should be in order to

make them more achievable. Gotsis and Kortezi (2013) and McPherson (2013) have applied

this concept into their recent research.

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3.4.2. Ethical paradigm and its implication

Understanding all ethical paradigms has facilitated the research process for all

researchers (Robson, 2002). There are many cases where researchers changed the data and

explained the results in an appropriate way, applied any means if needed in order to obtain

the best outcome as expected (utilitarianism). However, instead of using this teleological

view, my current research inclines to the view of the character of an action itself and using

apparent methods during the research process rather than taking the viewpoints of researchers

into account and considering them as a central stance (virtue ethics). Based on this, Kantian

ethics based on the deontological perspective are regarded as the best ethical standpoint for

the current research.

Based on the research project proposed and comprehensive understanding of the

philosophy, paradigm, ethical issues, there are many issues related to ethics that should be

considered in the study. As Saunders et al. (2009:184) stated that ethical issues related to

“questions about how we formulate and clarify our research topic, design our research and

gain access, collect data, process and store our data, analyse data and write up our research

findings in a moral and responsible way”. Therefore the ethical issues of the whole research

process should be considered comprehensively and equally (Healey, 1991). Firstly, the study

involves clarifying the research topic and designing the research. From academic

perspectives, it would be better if the topic is explored comprehensively and designed in an

appropriate way based on literature review and research designed by many previous good-

quality published papers. In this process, philosophy and paradigm reveal their significant

influence and their strongly-connected relationship with ethical issues (Wells, 1994).

Secondly, both secondary data and primary data (surveys, questionnaires), in which human

participants get involved, are used. When using secondary data, ethical issues might occur,

the sources of secondary data should be reliable, and how the data is stored should also be

checked in order to make all data collected credible. In addition, applying Kantian ethics lead

the research nature to be more about the character of an action, treating people involved as an

object to be exploited for our purposes is considered as totally wrong; it means that the

freedom of participants in the survey (joining without reluctance) and their personal

information and viewpoints need to be put in proper places and under careful usage with

respectable consideration. Thirdly, to avoid subjective selectivity and bias occurring during

the data collection process, strict standards will be set by the researcher. These actions will

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facilitate the reliability and validity of the research. Fourthly, analysing data by applying

many analysis tools (using SPSS, conducting multivariate analysis, exploring exploratory

factor analysis, confirmatory factor analysis and structural equation modelling might be

suitable for this study) could lead to breaking the law of Kantian ethics because researchers

can use different statistical methods and technique to get the best outcomes (Saunder and

Savulescu, 2008). This problem will be considered during my research process. Finally,

writing up the results could be significantly affected by the writer’s viewpoints, thanks to the

philosophy and paradigm that the research has followed; the writing process would be

apparent and would reveal its objective consequences. Besides that, to prevent all problems

raised, 18 ethical principles for research and the code of practice on research misconduct in

the guide for the code of ethics published by Hull University Business School (HUBS, 2005)

should be followed comprehensively (See Appendix 3.1 for research ethics approval letter

used for conducting this research).

3.5. Research process

As conducting any research, a research process is considered as a vital step to help

researchers understand and commit with a right research path. One of the main reasons for

considering it is that research can take more time with many related considerations. It is a set

of activities unfolding over time. During the research process, researchers might slightly

change or modify their research ideas, but it would be useful if they know their own research

objectives and have a specific plan for the research (Ghauri and Gronhaug, 2010). At

different stages, they might confront different issues, clarifying the research process will help

them perform tasks systematically and be able to check what is to be done at a particular

stage (Sekaran and Bougie, 2010). For example, researchers need to clarify and understand

their research objectives, exploit some necessary literature in order to support the research

process before collecting the data. A typical research process has been proposed by Ghauri

and Gronhaug (2010) (Figure 3.2). However, depending on the purpose of a research project,

these steps can be different. According to Morgan (1993), Pettigrew (1985), Bryman (1988),

in reality, the research process is not so orderly and sequentially presented as in Figure 3.2.

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Figure 3.2: The research process

(Ghauri and Gronhaug, 2010:30)

According to Saunder et al. (2016), researchers might need to follow the precise number

of stages to complete the research, but it might vary, normally they include clarification and

formulation of the topic, reviewing literature, choosing philosophical approach, designing the

research, collecting data, data analysis and writing up. The following research process onion

can visualise the above statement (Saunders et al., 2003:83; 2016:164). This onion

demonstrates the number of choices, including philosophical orientation, research

approaches, paradigms, strategies and steps that researchers can follow (Figure 3.3).

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Figure 3.3: The research process onion (Saunders et al., 2003:83; 2016:164)

3.6. The choice of research methodology

This research is conducted based on the typical question of “What factors affect X

(dependent variables) and at which level?” as well as exploring differences between groups.

As presented above, qualitative research is generally associated with the phenomenological

paradigm and quantitative methodology relates to positivism (Mangan et al., 2004).

Combined with the research objectives, this research is going to use mixed methods (as

mentioned above) in order to achieve and maintain the accuracy, reliability and integrity of

the research. The qualitative research includes semi-structured expert interviews, which will

help the researcher identify “strategic groups” within the Vietnamese supermarkets in order

to facilitate the subsequent comparison of groups; semi-structure interviewing consumers will

also help the researcher justify and validate her proposed research framework, with constructs

added after interviewing if required. The use of quantitative research in the form of

questionnaires will provide data which allows the researcher to answer the previously

mentioned question of “at which level”. Therefore, it should follow the steps mentioned in

the Cannon’s research (2004) (see Figure 3.4).

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Figure 3.4: Steps in the process of conducting a mixed methods study

(Adapted from Cannon, 2004)

After reviewing all previous literature related to customer loyalty in general and

customer loyalty in the supermarket sector in particular, and looking at the relationship

between variables affecting customer loyalty, the next step is to conduct a pilot study by

interviewing a number of customers and re-build the research model (Mentzer and Flint,

1997) then, develop measurables for these final variables in questionnaires before doing a

survey. There exists a reason why the above issues have been encouraged in many research

projects. All variables built from previous research might not be suitable with the current

research due to different objectives, samples and research methods; a pilot study via

interview can improve the level of validity of the research before doing specific structured

questionnaires.

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As explained from the beginning, the research focuses on the context in Vietnam, all data

collected will be in the Vietnamese market. For the quantitative phase, many steps will be

conducted before testing the hypothesis, such as checking the reliability and validity of all

data collected via analytical methods in SPSS, analysing EFA (exploratory factor analysis) to

remove duplicated variables. Besides that, confirmatory factor analysis can be applied due to

the existing of sub-variables in each variable; an analysis of SEM is also used in this research

in order to demonstrate the relationships between many variables.

The following figure (Figure 3.P) is going to summarise two phases that will be

conducted in this research:

Figure 3.P: Procedure of two phases conducted in this research

(Source: from the researcher)

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3.7. Research method: Phase One_ Step One_Expert interviewing

3.7.1. Chosen research strategies: semi-structured interview

It is clear that the research relates to factors affecting customer loyalty of different

strategic groups. Therefore, before investigating other issues, definition of strategic groups

and how supermarkets can be divided into their strategic groups should be explored. Besides

that, this study is going to collect data in Vietnam to examine the proposed research

framework, interviewing experts in retailing and the grocery sector is needed in order to

classify firms into a specific strategic group. This phase will allow the researcher to conduct

multigroup analysis later to investigate differences between groups (which can facilitate an

answer to research questions 4 and 5).

In general, a strategy has been regarded as “a plan of action to achieve a goal” (Saunders

et al.; 2016:177). Therefore, a research strategy refers to a plan of how researchers conduct

their research to achieve their research objectives. According to Denzin and Lincohn (2011),

it is all about methodological issues which is a link between a research philosophy and choice

of methods used to collect and analyse collected data. It is clear that the chosen research

strategy is guided by research questions and must meet research objectives.

The Phase One interviews are regarded as qualitative research interviews. There are

many available types of interview. Converse and Schuman (1974:53; cited in Denzin and

Lincoln, 2000:650) noted that “There is no single interview style that fits every occasion or

all respondents”. However, a semi-structured interview is the choice of this research due to its

natural match to this research’s interest. Reasons are going to be explained as follows.

According to Doody and Noonan (2013), Saunders et al. (2016), considering the nature of

semi-structured interviews, researchers might need to prepare a clear list of questions and the

checklist of specific questions related to a topic that they are going to investigate. Based on

this, interviewers can drive a conversation and explore deeply all main points. Depending on

the flow of a conversation; the order of these structured questions can be changed. During the

interview process, interviewers can also add some further questions, such new questions are

obviously not presented in the interview guide but the interviewers create new questions

based on picking up on things said by interviewees and the interviewees have a great deal of

leeway in how to reply, meaning they are free to answer in their own styles while the

researcher can prompt on the main issues, the research’s viewpoints and let interviewees give

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ideas to explore whether new insights have been demonstrated or not. In this way, some areas

which had not previously being considered will be addressed fully. These strategies can be

beneficial to the analysis process as the researcher can compare and contrast across the case.

With unstructured interviews, it can be easy to lead to a huge range of topics and

answers that can impede the analysis process due to lack of information focus; the researcher

could then not easily compare or contrast interview results (Collis and Hussey, 2009). Group

interviews could not be conducted in this research because the respondents are to be found at

different locations and they offered different schedules for participating in the research.

There are different types of semi-structured interviews; in this research, an interview

may be conducted on a one-to-one basis via three available options such as “face-to-face”,

telephone, internet-mediated (electronic) interviews. With PHASE ONE, named “expert

interviewing”, face-to-face is considered the best choice when the interviewer can explore

more deeply the expert’s comments about retail strategic groups in Vietnam as well as his/her

point of view about the Vietnamese retail market and the development direction.

3.7.2. Sample and contacting the experts

The objective of Phase One is to group the Vietnamese supermarkets into different

strategic groups. Many methods can be used to obtain such observations as an analysis of

firms’ development strategies and resources (strategic theories presented in Chapter 2,

section 2.1). Besides that, interviewing some experts in strategy in the Vietnamese retail

industry can create more reliable findings. In this thesis, the researcher is going to combine

these two techniques.

Teddie and Tashakkori (2009) suggest two types of sampling that researchers can use,

including probability and non-probability (purposive) sampling. Differences between the

two are presented below (Table 3.4).

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Table 3.4: Comparisions between purposive and probability sampling techniques

(Teddie and Tashakkori, 2009: 179, adapted by Chaisurayakarn, 2015:115)

The main objective of this phase is to group Vietnamese supermarkets into correct

groups and the potential interviewees will be experts in retail and stategy. What is needed is

experts who can most likely offer valuable information. Based on the differences and the

research purpose, a non-probability method which includes “the purposive expert sampling”

will be chosen (Bird et al., 1996). According to Sekaran and Bougie (2011), Oliver (2006),

purposive sampling is the method where respondents are selected based on a variety of

criteria which can include their relevance, their specialist knowledge of the research topic or

the willingness to participate in the research. It means that after understanding the purpose

of the research, the researcher will identify a predetermined target group.

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There are four purposive sampling techniques, including convenience sampling,

judgmental sampling, snowball sampling and quota sampling techniques, differences

between these four techniques and their advantages are presented in Table 3.5. In this phase,

judgmental sampling technique with some specific characteristics is applied due to the

technique’s nature presented in Table 3.5 and the researcher will use her judgment to contact

an expert in retailing. The researcher has a good knowledge of strategy, based on good

academic and business experience in Vietnam.

Table 3.5: Advantages of non-probability sampling techniques

(Source: Bryman and Bell (2015); Malhotra et al. (2012), Chaisurayakarn (2015:95))

3.7.3. Interviewing guide development

There are two areas which will be discussed during the interviewing process, including

strategic groups and customer loyalty. “The key to a successful interview is careful

preparation” (Saunders et al., 2016:401). They indicate that the “five Ps” can be remembered:

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“prior planning prevents poor performance” (Saunders et al., 2016:401). Therefore, before

conducting interview, there are many steps that should be undertaken.

3.7.3.1. Preparing an interview guide

An interview guide is used to refer to “the somewhat more structured list of issues to be

addressed or questions to be asked in semi-structured interviewing” (Bryman and Bell,

2015:486). Bryman and Bell (2015) also suggest that the prepared interview questions should

not be too specific because during the interviewing process, alternative avenues of inquiry

might arise, and closed questions indicate that “such premature closure of your research focus

would be inconsistent with the process of qualitative research” (Bryman and Bell, 2015:486).

If more information is revealed during the interview, researchers can use it later if needed. In

addition, Byman and Bell (2015:486) suggest that the researchers should consider “What do I

need to know in order to answer each of the research questions I am interested in?”. It means

that an appreciation of the viewpoints of interviewees is important and accordingly the

questions asked need to cover the interests of both interviewers and interviewees. Therefore,

the interview guide should create a certain amount of order in the research topics but the

researcher also needs to be prepared for the order to be changed due to the unpredictable flow

of answers from interviewees. Formulating interview questions can help researchers lead the

main flow and get the useful or required information. The following figure (Figure 3.5) can

suggest the steps to be used in formulating questions for an interview guide:

Figure 3.5: Formulating questions for an interview guide (Bryman and Bell, 2015:489)

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There are some elements that interviewers can consider before the interview. Making

sure the researcher is familiar with the interviewee’s work; and life in order to facilitate the

quality of the interview. For instance, the demographic questions are not aimed in this case

but knowing the information can help the interviewer understand some basic background

about the participants. In addition, preparing a good digital recorder is also important because

many interviews are unsuccessful due to poor recording or technogical mistakes; ensuring a

quiet location for interviewing is also important. During the interview, interviewers should

try to use simple/relevant and transparent questioning techniques, and should avoid using

complex or difficult theoretical terms. The interviewer should also take notes of a general

kind such as name, age, gender, education level and so forth, to provide context. After the

interview, interviewers should take notes about how the interview went/where the interview

has been conducted (including place (offline) and online if needed) and all related matters

that arose during the interview (Bryman and Bell, 2015). Besides that, managing logistical

and resource issues needs to be considered and prepared for, such as interview scheduling,

interview management, recording and transcription issues, time available, how long the

interview should take and how much it will cost.

There are some techniques available which may enhance the quality of data collected.

After interview, interviewers should give interviewees an opportunity to comment fully about

the topics covered or raise any related issues that the interviewee believes might be

interesting or beneficial to the research; this process is referred to as “catch-all” or

“doorknob” questions. Some researchers advise that taking notes during interview or after

leaving the interview can be beneficial in many ways (Bryman and Bell, 2015; Saunder et al.,

2016). They also suggested that interviewers can test their understanding by summarizing all

information provided during interview and asking interviewees to comment or check if the

summary is correct, and interviewees can be invited to add further points at the end. This

process can avoid bias or misinterpretation of results. The ideal situation would be if

interviewees are able to proofread interview transcripts in order to check their accuracy.

The interviews will be conducted in Vietnamese, and will then be translated to English

for analysis; the researcher intends to perform the initial translation then have it checked to

improve accuracy.

There are some main questions that should be covered in all qualitative interviews

regardless of the core topic (Bryman and Bell, 2015, adapted by Rafi-Ul-Shan (2015:129);

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Saunders et al., 2016). The interview should be started with an introduction; researchers

should demonstrate clearly the purpose of the interview and request the interviewee’s

permission for recording. The following guide should be applied during interviewing process

(Figure 3.6):

Figure 3.6: Some main questions that should be covered in all qualitative interviews

(Bryman and Bell, 2015; adapted by Rafi-Ul-Shan (2015:129); Saunders et al., 2016)

This guide can facilitate the interview process and improve the quality of information

collected; in the next section, core questions will be discussed.

3.7.3.2. Core questions

There are three main themes in this interview, including the current retail situation,

strategic groups and customer loyalty. The intended questions are related to these themes in

order to explore experts’ views and probe for sub-topics. There are 6 questions which are

presented in the above three main themes (2 main questions per theme). The first question in

the interview guide is used to investigate the brief comments of experts about the current

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state of the Vietnamese retail industry. The purpose of the second question is to investigate

the state of the Vietnamese supermarket sector as well as the competitive environment. Then,

at theme 2- question 3, experts will be asked to comment how firms are grouped into strategic

groups in general as well as a specific technique that can be use. The next question in the

interview guide was created to ask the specialists about grouping Vietnamese supermarkets

into different strategic groups by giving him/her a prepared list of current main Vietnamese

supermarkets. During the answering of this question, specialists will be asked to explain why

he/she chose to allocate supermarkets to specific strategic groups. For theme 3, the experts

will demonstrate their wisdom and knowledge of customer loyalty based on the designed

questions, specifically, question 5: “Based on your previous own research and experience,

which possible factors might affect customer loyalty?”. With this question, the interviewer

will listen and take note of experts’ comments, then the proposed research framework created

at CHAPTER 2, section 2.5.13.2 should be shown in order to elicit further information from

the experts. The interview will be ended by the sixth question: “What is the linkage between

customer perceived value, customer satisfaction and customer loyalty?”. These two questions

in Theme 3 will help in exploring and understanding more about the relationship between the

many factors which will be tested later under the experts’ points of view. All of the six main

questions which will be asked during this interview process can be presented as follow:

The current retail situation

Question 1: Can you give me a brief review of the overall situation in the Vietnamese retail

industry?

Question 2: What about the situation in the supermarket sector as well as the competitive

environment? Do you have any comments?

Strategic groups

Question 3: Normally, how can we group firms into their right strategic groups? Which

techniques can we use?

Question 4: Based on the Table 2.3.1, there are 12 supermarkets in Vietnam, how can we

group them into different strategic groups? Why?

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Customer loyalty

Question 5: Based on your previous own research and experience, which possible factors

might affect customer loyalty?

Question 6: What do you consider to be the linkage between customer perceived value,

customer satisfaction and customer loyalty?

Therefore, the following table presents questions for interviewing:

Question Explanation

PHASE1_Q1 Participants were asked to give a brief review about the overall

situation of the Vietnamese retail industry. Besides that, the

interviewer asked about the current role traditional markets in

Vietnam and how cultural factors affect consumer behavior. The

interviewees are free to present his/her viewpoints.

PHASE1_Q2 Participants were asked to give their viewpoints about the current

situation of supermarket sector as well as their competitive

environment in Vietnam.

PHASE1_Q3 Participants were asked for their opinion of techniques that can be

used to group firms into their right strategic groups.

PHASE1_Q4 Participants were asked for groupping 12 main Vietnamese

supermarkets to their right strategic groups. The interviewer show

the list of supermarkets (see Table 2.3.1). The respondents were

also asked the reasons about their choices.

PHASE1_Q5 Participants were asked to present which possible factors might

affect customer loyalty based on their professional.

PHASE1_Q6 Participants were asked to present the linkage between customer

perceived value, customer satisfaction and customer loyalty.

Table 3.6: Structural of semi-structured interview protocol in Phase One (Step One)

See Appendix 3.2 for full guide of expert’s interviewing.

3.7.3.3. Translation and back translation

Back translation is a good technique which has been widely applied by researchers to test

the accuracy of translations in order to avoid mistakes occurring during the translation

process, particularly in cross-cultural research (Douglas and Craig, 2007; Saunders et al.

(2016). It is crucial if the questionnaires are to have the same meaning to all respondents. For

this reason, Saunders et al. (2016) suggested to follow up the guidelines of Usunoer (1998).

These guidelines presented that researchers should be aware of many criteria when

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translating, including lexical meaning, idiomatic meaning, experiential meaning, grammar

and syntax. In this study, all of the above criteria were carefully applied to guarantee that the

translating process was deployed correctly. Usunoer (1998) also outlined some techniques for

translating, including direct translation, back-translation, parallel translation and mixed

techniques. The following table (Table 3.7) will summarise the approaches, advantages and

disadvantages of each technique.

Direct translation Back-translation Parallel translation Mixed-techniques

Approach Source questionnaire

to target questionnaire

Source questionnaire


to source

questionnaire;

comparison of two

new source

questionnaires,

creation final version

Source questionnaire


by two or more

independent

translators; comparison

of two target

questionnaires,

creation final version

Back-translation

undertaken by two or

more independent

translators, comparison

of two new source

questionnaires, creation

final version

Advantages Easy to implement,

relatively inexpensive

Likely to discover

most problems

Lead to good wording

of target questionnaire

Ensures best match

beween source and

target questionnaires

Disadvantage Can lead to many

discrepancies

(including those

relating to meaning)

between source and

target questionnaire

Requires two

translators, one a

native speaker of the

source language, the

other a native speaker

of the target language

Cannot ensure that

lexical, idiomatic and

experiential meanings

are kept in target

questionnaire

Costly, requires two or

more independent

translator. Implies hat

the source questionnaire

can also be changed.

Table 3.7: Translation techniques for questionnaires

Source: Developed from Usunier (1998), adapted by Saunders et al. (2016:465)

According to Malhotra et al. (2012) “Back translation is a translation technique that

translates a questionnaire from the base language to the one into which the questionnaire is

being translated. This version is then retranslated back into the original language by

someone whose native language is the base language”. In this research, translation/back

translation was applied. The targeted respondents of this research are Vietnamese. Therefore,

the languague used in the questionnaire should be translated into Vietnamese. Performing a

direct word-for-word translation might prove problematic; therefore thanks to the good

knowledge of academic research and the English level reached, the researcher has the ability

to translate the whole questionnaire to Vietnamese by herself. She then employed a highly

experienced certified and qualified translator to check. At the same time the researcher asked

her peers who have the same academic level and good English to double check. The next step

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was that the questionnaire had been delivered to another independent professional translator

to translate the questionnaire back to English. In this step, face-to-face discussion between

the researcher and a language expert was needed in which the researcher was able to explain

some business terminology to the language expert to make sure that the final Vietnamese

version (a target questionnaire) correctly reflects the right content of the original English

version (a source questionnaire). In order to ensure the accuracy and validity of the

translation process, the language expert should compare differences between the original

English version and the later translated version: if there are no differences between the two

versions, the Vietnamese version can be used to distribute to respondents. If there are

differences between versions, corrections should be made until the content of the Vietnamese

version matches the original English version. It needs to be noted that the source version

should be initially checked by a native speaker before conducting a translation process.

3.7.3.4. Conclusion

The above interview guide will be applied in Phase One, it presents some main steps to

formulate the questions, how the interview is to be conducted, some techniques to enhance

the quality of data being collected, what kind of main questions will be covered and so forth.

The following part will demonstrate the data collection and analysis strategy.

3.7.4. Data collection

Regarding data collection, there are four steps that can be applied in this phase. The

interview protocol will cover the main themes relating to strategic groups and customer

loyalty. Then, deciding the sampling type and interviewing appointments are the next steps.

As presented above, the judgmental sampling technique will be used because the respondents

should be retailing and strategy experts. It means that the information provided by them is

highly valuable and reliable. Making the appointments and getting respondents’ approval can

be done via email, telephone. The place and time of interview is mainly depending on the

respondents’ choice. The next step will be conducting an interview and the interview guide

will be presented. The final step in this phase is transcript, coding and analysis (Figure 3.7).

Each interview was fully transcribed by the researcher in a Word version in both

Vietnamese and English.

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Figure 3.7: Data collection processes in Phase One

Adapted from Churchill and Lacobucci (2010)

3.7.5. Data analysis

The interviewing time was one hour and thirty minutes. According to Ghauri and

Gronhaug (2002), Malhotra et al. (2012), Chaisurayakarn (2015:99), there are four steps that

should be covered in the qualitative approach. At the first step, the data collected from

interviews will be completely transcribed. The next step is data reduction, it refers to the

process of selecting useful data for research. In this step, the different categories will be

divided into different groups, named data coding. Data display and data verification are the

two final steps; presenting the results by comparing, analysing and discussing the

phenomenon. This semi-structured interview was conducted on 10 March 2018, it was audio-

recorded and the interviewer also took notes during the interview.

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Table 3.8: The process of data analysis

(Source: Adapted form Ghauri and Gronhaug (2002), Miles et al. (2014), Malhotra et al.

(2012), Chaisurayakarn (2015:99))

3.8. Research method: Phase One _Step Two_Supermarket consumer interviewing

Reasons why this phase should be conducted are going to be presented. After literature

review, the research framework has been proposed. However, it should be noted that

depending on the market, there are different factors which might affect customer loyalty and

based on some suggestions of Cannon (2004) about using a mix method. Interviewing can

qualitatively justify whether the proposed research model is ready for collecting quantitative

data or not. Therefore, conducting supermarket consumers’ interviewing will help the

researcher add some more constructs, as to what can affect customer loyalty in the

Vietnamese market if needed - and information collected in this phase would be better used

to explain the relationship between constructs later on (Phase Two).

3.8.1. Sample size and contact

Differences between probability and non-probability techniques and Table 3.5 present

advantages of non-probability sampling techniques. Based on purposes of this phase on

investigating consumers’ loyalty behaviour or which factors might affect customer loyalty in

order to justify the proposed research framework, purposive sampling will be chosen and

snowball sampling techniques applied. In this technique, the researcher will actively plan

which supermarket’s consumers are going to be intereviewed based on region, income,

educational level, age range and gender and so forth. It is convenient and the researcher can

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ask interviewees to introduce further interviewees if possible with different demographic

backgrounds, so that later information collected can be more reliable. As recommended by

Saunders et al. (2016) and Creswell (2013), researchers should expect to undertake from 5 to

30 interviews. In this phase, about 20 interviews will be conducted. These twenty

supermarket consumers have been chosen based on the differences of geographical areas, age

ranges, income, frequency of consumption, education levels and so forth. As is the nature of

snowball sampling techniques, the researcher made contact with people that she knows and

asked for interviews and requests for introductions of further potential participants. Lists of

interviewees will be presented in Chapter 4.

3.8.2. Interviewing contents

As explained in the previous part (methodology), semi-structured interviews will be

applied in this phase. The steps to create the interview guide were previously noted. The

interview contents were generated based on the main objectives of this research and the main

interview themes derived from previous reviewed literature. “Without at least some focus,

your interview will lack a sense of direction and purpose” (Saunders et al., 2016:402).

According to Saunders et al. (2016), starting with listing a set of themes that reflect the

variables being studied is a crucial step, followed by creating a question in each theme.

During creating the guide, researchers should try to ensure a logical order of questions and a

readily comprehensible language.

There are 35 questions which probe supermarket consumers’ perception about their

loyalty level, which main factors can affect their loyalty as well as exploring other new

factors which have not been mentioned in the literature review and the proposed research

framework (see figure 2.5.19). Back-to-back translation techniques will also be applied in

this phase (See Appendix 3.3 for full guide to supermarkets’ consumer interviewing).

3.8.3. Telephone and Internet-mediated interviews

Most in-depth or semi-structured interviews occur on a face-to-face basis. However,

thanks to the development of video telephony, interviews can be conducted via a video/audio

calling service. Besides that, internet-mediated interviewing is also considered, using mobile

and computing technologies via the internet (Saunders et al., 2016). There are many

advantages and disadvantages of these interviewing methods. Reseachers can easily reach

different geographically dispersed populations that they wish to interview with low cost and

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flexible time. Disadvantages include technical issues. Applying the nature and objectives of

this research, 40% of interviews will be telephone and Internet-mediated interviews because

the researcher conducts the interviews with 21 supermarket consumers across the country.

There are 5 interviews being conducted face-to-face and 16 interviews via telephone and

Internet-mediated approach.


Due to the research objectives and in order to answer the five main research questions,

quantitative methods will be dominantly used, the researcher is not going to use Nvivo for

data analysis in this phase, comparision on cross cases will be used.

3.9. Research method: Phase Two_ Questionnaire survey

As briefly presented in Figure 3.P, there are two phases being conducted in this

empirical study. Step one of Phase One aims to divide Vietnamese supermarkets into their

right strategic groups by interviewing experts in the retailing industry in order to facilitate

future analysis (differences between strategic groups - answering question 4). Step two of

Phase One (supermarket consumers’ interviewing) aims to reveal factors which might affect

customer loyalty in the Vietnamese market. As a result, if some more factors are revealed,

they will be added to initial proposed questionnaires and prepared for survey in order to

collect quantitative data and answer all research questions.

3.9.1. Survey Questionnaire

The survey strategy is usually associated with a deductive research approach. The

purpose of conducting surveys might vary, but it is normally used to answer “who”, “what”,

“where”, “how much” and “how many” questions. In this way, a survey is applied for

exploratory and descriptive research and can clarify how respondents or the population

perceive/behave or think in relation to a specific issue through many quantitative analysis

tools (Saunders et al., 2016). Surveys and questionnaires are the dominant data collection

methods in business studies. The benefits of this method are to allow researchers to collect

and analyse data systematically via a formulated and structured question. According to Gill

and Johnson (1991), before conducting a survey, researchers should re-check and can follow

a pattern as suggested below (Figure 3.8):

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Figure 3.8: Planning a survey (Gill and Johson, 1991:76-7)

However, surveys hold some potential weaknesses in which low response rate can be

considered, this problematic issue might reduce the ability to generalise the results to the

entire population (Snow and Thomas, 1994); another issue can relate to response errors due

to some ambiguous wording in questionnaires (Mangione, 1998).

3.9.2. Initial design and planning

The objective of initial design and planning is to make sure that a survey questionnaire is

strongly linked to the research questions, research objectives and all literature review

previously presented. Therefore, deciding what data needs to be collected is crucial, “the

questionnaire offers only one chance to collect the data as it is often difficult to identity

respondents or to return to collect additional information” said by Saunders et al. (2016:444).

The steps of this stage include sampling frame identification, sample size and sampling

design.

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3.9.2.1. Sampling frame identification

Saunders et al. (2016:277) defined “the sampling frame for any probability sample is a

complete list of all the cases in the target population from which your sample will be drawn”.

The objective of this research is concerned with supermarket consumers at five main cities

regardless of age range, gender, education level, income and other background issues.

Therefore, the sample frame is all supermarket consumers at the targeted cities. However, it

seems impossible to generate the complete list of supermarket consumers in the target cities,

the intended sampling frame can be drawn from this explanation that there are a huge number

of people who are using supermarkets in the targeted cities.

3.9.2.2. Sample size

After literature review part and interview, there are 19 factors listed which might

demonstrate the multi-relationships between the researched issue, including in-store logistics,

service quality, e-service quality, product quality, price, customer service, customer

experience, brand experience, store image, corporate image, loyalty programmes, switching

cost, alternative attractiveness, store accessibility, corporate social responsibility, promotion

effects, customer perceived value, customer satisfaction and customer loyalty. However,

Phase 2 has revealed two other factors which should be considered as well, including TRUST

and HABIT. So there are 21 factors in total, in the case of every single factor is evaluated by

3 variables as Peter (1979) indicated that multiple-item scales are constructed to increase

validity and reliability, the minimum size of this step should be 21*3*5= 315 because

according to Hair et al. (2010), the number of the sample size should be five times bigger

than the number of variables. However, after PHASE 1, there are five strategic groups in the

Vietnamese supermarkets. In order to compare and contrast differences between the five

strategic groups, the minimum size should be 315*5= 1,575. As explained, there are five

different main areas in Vietnam where supermarkets seem to be significantly developed;

these areas can be a good representative in main urban cities in Vietnam, including Ha Noi,

Da Nang, Ho Chi Minh, Binh Duong and Can Tho. In fact, there are 111 variables as

presented at Table 3.11 (next part). Therefore, total sample size should be at least 111*5*5 (5

different strategic groups) = 2,775. When the data collection process is completed, there

might be some questionnaires which could be removed from the whole data set due to

incompletion or wrong formatting. Therefore, it should be recommended that the researcher

might expect to get 3,000 questionnaires from 5 different cities.

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3.9.2.3. Sampling design/sampling selection

Saunders et al. (2016) demonstrated available sampling techniques that researchers can

use, including probability or representative sampling and non-probability sampling. “With

probability samples, the chance or probability of each case being selected from the target

population is known and is usually equal for all cases” (Saunder et al., 2016:275). And “For

non-probability samples, the probability of each case being selected from the target

population is not known” (Saunder et al., 2016:276). Table 3.5 revealed the differences

between probability sampling and non-probability sampling, because of the nature and

objectives of this research with a large number of questionnaires needing to be collected, the

probability sampling technique will be applied. There are four probability sampling

techniques, which are summarised in Table 3.9, used to choose the sampling. The advantages

of each technique are also demonstrated. According to Saunders et al. (2016:290) “Stratified

random sampling is a modification of random sampling in which you divide target population

into two or more relevant and significant strata based on one or a number of attributes”.

Based on the above explanation (section 3.9.2.2), around 555 samples should be collected in

each city in order to get the target of 2,775 samples (see section 3.9.2.4 below), stratified

random sampling relates to dividing the target population and choosing a random sample.

After considering the nature of each technique and its advantages, stratified random sampling

will be used in this phase (PHASE TWO).

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Table 3.9: Advantages of Probability Sampling Techniques

(Source: Bryman and Bell (2015), Malhotra et al. (2012), Saunders et al. (2016), adapted by

Chaisurayakarn (2015:104))

3.9.2.4. Locations selected for the study

The empirical research has been conducted in five huge markets in Vietnam, including

Ha Noi, Da Nang, Binh Duong, Ho Chi Minh and Can Tho. There are some reasons why

these cities have been chosen. Most supermarkets are located in these areas (see Table 2.3.1).

Therefore, total revenues of the Vietnamese supermarket sector will be mainly generated

from the above mentioned five cities. Besides that, these areas seem to have a different

culture and consumption style from different parts of the country. In particular, Ha Noi

represents the northern side, Da Nang is from the middle of the country, Ho Chi Minh city

and Binh Duong represent the south side, Can Tho is a big city in the Mekong Delta. If the

data has been collected from these big markets and different cultures, it might be beneficial

for explaining and revealing the whole picture of the Vietnamese supermarket sector.

3.9.3. Scale Development, Reliability, Validity and replication

As known, research philosophy and paradigms can shape the research process and the

way the research should be conducted. It also affects the validity and reliability of research

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findings. In every research, research quality issues have always been regarded as one of the

top priorities, how to obtain good quality data is part of this process. According to Ghauri and

Gronhaug (2010), the quality of collected information depends highly on the procedures of

measurement applied during the data gathering period. Without measurement, it seems to be

difficult to comment on business behaviour or any business phenomena (Hair et al., 2011). In

other words, scales of measurement should be scrutinised in order to improve reliability and

validity.

3.9.3.1. Scale development

The nature of this research is associated with exploring many possible factors

influencing customer loyalty and at which levels these factors affect loyalty or relationships

between variables. From a psychological perspective, the perceived value of customers as

well as their feelings are necessary and hold a vital role during a data measuring process. The

broadly applicable scale development paradigm proposed by Churchill (1979) has been

developed by Gerbing and Anderson (1988), Nunnally and Bernstein (1994) and McMullan

(2005), they proposed five stages that researchers can apply to develop the loyalty scale.

What follows is based on much previous literature on customer loyalty reviewed by Bearden

et al. (1993) and De Vaus (1996) (see Figure 3.9).

Figure 3.9: Stage in the development of the loyalty scale (McMullan, 2005: 473)

A scale is defined as “a measurement tool that can be used to measure a question with a

predetermined number of outcomes” (Hair et al., 2011: 215). There are many types of scales

that can be used in business such as nominal scale, ordinal scale, interval scale, ratio scale,

but it is clear that these types of scale can be divided into two groups including metric

(Likert, numerical, semantic differential, graphic ratings) and non-metric scale (categorical,

rank order, sorting, constant sum) (Hair et al., 2011). Based on research objectives and the

nature of this research, Likert scales, which “are generally treated as interval scales” (Sekaran

and Bougie, 2013:221), will be used. Likert scales often use “a five-point scale to assess the

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strength of agreement or disagreement about a statement” (Hair et al., 2011: 221). At each

point, researchers can develop a specific label to demonstrate the feelings of respondents.

Some researchers use a seven-point Likert scale to emphasise a variety of levels of feelings or

respondents’ agreement. If researchers present many statements which relate to one concept

and then combine all these individual statement ratings, the result is referred to as a

summated rating scale (Hair et al., 2011) which is widely used in business research (Sekaran

and Bougie, 2013). Besides, another version of a Likert scale named “behavioural intention

scale” which has been used in business can help researchers explore how likely customers are

to indicate some types of behaviour. For example, with the question “how likely are you to

purchase a new laptop in the next 12 months”, researchers use a seven-point Likert scale from

1 to 7 to demonstrate from “Not likely at all” to “highly likely” (Hair et al., 2011).

Braunsberger and Gates (2009:220) described a basic Likert scale as follows: “the left-hand

anchor read “greatest disagreement”, the scale midpoint “neither agree nor disagree”, and the

right-hand anchor “greatest agreement”. In questions which are assessed by the scale point,

respondents are asked to mark in the space on the scale point to express their choices.

3.9.3.2. Reliablility - Replication - Validity

Bryman and Bell (2015) indicated three of the most important criteria for the business

research’s evaluation, reliability, replication and validity. Sekaran and Bougie (2013)

presented the diagram of testing goodness of measures as doing research (Figure 3.10).

Figure 3.10: Testing goodness of measures-forms of reliability and validity

(Sekaran and Bougie, 2013:226)

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Reliability

Reliability is concerned with the consistency of the research finding, “a survey

instrument (questionnaire) is regarded as reliable if its repeated application results in

consistent scores” (Hair et al., 2011: 233). It means that the findings might be unchanged or

slightly changed across the research. In order to be reliable as a scale, questions which will be

answered by respondents should be consistent and be highly correlated. Malhotra et al.

(2012) and Veiga Dias et al. (2016:) have also indicated that reliability, which “consists in

assessing to what extent a scale is able to produce consistent results when systematic

repetitions are done” when “the measurement procedure is free of random mistakes”, should

be considered properly during the research process. Hair et al. (2011) and Malhotra et al.

(2012) indicated that there are three categories which should be noticed in terms of concern

about reliability.

Stability of measures presents “the ability of a measure to remain the same over time”

(Sekaran and Bougie, 2013:229). There are two tests of stability, namely test-retest reliability

and parallel-form reliability. Test-retest reliability is applied by repeated measurement of the

same group of respondents in terms of other factors remaining unchanged in order to check

whether a measure is stable, then researchers can compare how similar these results are, if

they are relatively similar or similar, it can be confirmed that the findings reach a high test-

retest reliability. However, in reality, it is sometimes not practical to have the same groups of

respondents taking a survey twice. Besides that, during the survey period, even the same

respondents answers might be different due to being influenced by other external factors, for

example, their feelings might change at two different survey dates. Parallel-form reliability

can be used to solve the above indicated problematic issue. It was first introduced by Mitchell

(1996) under the name of “alternative form”. In order to assess this type of reliability,

researchers can develop two equivalent forms of the construct, both forms having comparable

items and the same response format; if both results are highly correlated, it can be concluded

that the measures are reasonably reliable.

Internal consistency reliability is used to assess the reliability of a set of items (named “a

summated scale”) by investigating its homogeneity. In other words, these items should “hang

together as a set” (Sekaran and Bougie, 2013:229). Consistency can be assessed through the

interitem consistency reliability and split-half reliability tests. Interitem consistency reliability

is a test of the consistency of respondents’ answers to all the items in a measure. For

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example, asking customers three questions related to their satisfaction levels, returning and

recommendations to friends about specific restaurants, if they are highly satisfied, they

should mark “definitely return” or will “definitely recommend to friends”, there are

consistencies between the respondents’ answers, the measures are considered as reliable. The

test of interitem consistency reliability include Cronbach’s coefficient alpha (Cronbach,

1946), which is used for multipoint-scaled items, and the Kuder-Richardson formulas

(Kurder and Richardson, 1937), used for dichotomous items. In these tests, the higher the

coefficients, the better measuring instrument. Hair et al. (2011) suggested that if the alpha

coefficient is higher than 7, the strength of association is regarded as good, it means that “the

questions combined in the scale are measuring the same thing” (Saunder et al., 2016:451).

The split-half reliability test refers to “the correlations between two halves of an instrument”

(Sekaran and Bougie, 2013: 229). In other words, researcher can randomly split into two

equal groups of scale items and examine their correlations and the higher the correlations, the

better the reliability. SEM reliability is evaluated by means of the square of the estimated

correlation value (R2), the value of construct reliability is computed from the squared sum of

factor loading (L) for each construct and the sum of the error variance terms (e) for a

construct. Furthermore, the average variance extracted (AVE) can be used to test a reliability.

It is measured as the total of squared standardised factor loading (L) divided by the number of

items (n). According to Hair et al. (2010), AVE should be equal to or higher than 0.5.

Validity

Validity is a test of how well a developed instrument can measure the right concept or

whether a variable can reflect properly the concept that researchers want to explore.

Regarding the quality issue of the research, the term of validity refers to “the validity of the

measurement instrument itself” (Sekaran and Bougie, 2013:225). There are several types of

validity test being used to examine the goodness of measures. Bryman and Bell (2015)

suggested six available applicable tests, including faced validity, concurrent validity,

predictive validity, construct validity, convergent validity and discriminant validity.

However, Sekaran and Bougie (2013) categorised the above indicated tests into three groups

(Figure 3.6): logical (content) validity, criterion-related validity, and congruent (construct)

validity.

Logical validity (content validity) ensures that the developed measures through previous

literature conclude an adequate and representative set of items that can reflect the concept. In

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this research, pre-testing the measurement can be used to determine content validity by

sending the questionnaire to a small number of respondents for review before sending to all

participants. Face validity refers to some items that researchers thought that it could measure

the concept. In reality, some researchers do not treat face validity as a part of content validity.

Crocker and Algina (1986) suggested that researchers might exploit the four following steps

in order to effectively assess content validity: identify the research’s interest area, collect

resident domain experts, develop applicable matching methodology, then analyse the findings

from the matching task. Exploratory factor analysis is often used in this case to filter out or

reduce unnecessary variables, improve the research’s validity. Criterion-related validity is a

test being used to measure how well the test scores to some specific criterion. The criterion

can be another test measuring close to the same thing as the test being evaluated is purported

to measure or some type of outcome (Sekaran and Bougie, 2013). For example, test for

leadership skills will match the test scores with the traits and attributes associated with known

leaders. Criterion related validity is classified into either predictive validity or concurrent

validity. Predictive validity relates to the criterion being located in the future. Concurrent

validity is established when the predictor and criterion data are collected simultaneously and

“when the scale discriminates individuals who are known to be different; that is, they should

score differently on the instrument” (Sekaran and Bougie, 2013:226). For example, working

behaviour between two different work ethic groups should be different, if the same score is

the result, it can be clear that the research validity is low. Construct validity refers to how

well the result attained from the test measure used fit with previous related theories that the

test is designed.

Sekaran and Bougie (2013) stated that there are two different types of validity test in this

category, including convergent validity and discriminant validity. Convergent validity is

established when the scores obtained from two independent measurements presenting the

same concept are becoming highly correlated (Sekaran and Bougie, 2013; Malhotra et al.,

2012). There are many ways to investigate the convergent validity of research. In this

research, a factor loading, the average variance extracted (AVE) for the item loading on a

construct will be examined. High factor loading might imply high convergent validity; the

coefficient of a factor loading should be higher than 0.5 and that of AVE can be acceptable if

above 0.4. Besides that, composite reliability (C.R) is also a convergent validity indicator; the

C.R value should be 0.7 or higher, in some cases equal or higher than 0.6 is acceptable (Hair

et al., 2010).

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Discriminant validity is “the extent to which a scale does not correlate with other

constructs from which it is supposed to differ” (Grant, 2003:202; Churchill, 1987; Malhotra

and Birks, 2000). Testing for discriminant validity is very important for research in terms of

guaranteeing an absence of overlap between measures of constructs (Bryman and Bell, 2015),

it means that this test “provided support for its distinctiveness” (Little et al., 2012:417).

According to Hair et al. (2010), discrimimant validity is supported when the AVE for a

construct is higher than the square correlation (R2) between that construct and other

constructs.

Replication

Replication might happen when researchers choose to replicate the findings of others.

There are many reasons which can explain why researchers may do this, such as there being a

gap or an ambiguous mind about previous research findings due to an external effect and

different markets or research environment. Bryman and Bell (2015:50) stated “if a researcher

does not spell out his or her procedures in great detail, replication is impossible”, they also

indicated that replication in business research is not common, but it still happens. For

example, Burawoy (1979) found by accident that his research using case study analysis in a

US factory has been investigated by Donal Roy three decades earlier, and then he thought

about treating his research work as replication. Burawoy (2003:650) wrote “I knew that to

replicate Roy’s study would not earn me a dissertation let alone a job…In academia, the real

reward comes not from replication but from originality”. Therefore, when planning research,

researchers should carefully consider whether their research replicates the work of someone

else.

3.9.4. Triangulation

Triangulation is highly recommended by researchers in any business research in order to

increase the quality of research, such as the level of validity and reliability (Bryman and Bell,

2015). As Denzin (1978:294), triangulation is defined as “the combination of methodologies

in the study of same phenomenon”, in other words, it refers to the use of different research

approaches, methods, techniques in the same study to help in reducing the bias level in data

sources, producing more objective and valid results.

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3.9.5. Questionnaire Design and questionnaire construction

It can be noted that well-designed questions are the skeleton of any good research study.

Steps which can be followed to create the questionnaire are quite similar to the protocol at

Phase 1 (Figure 3.12). After Phase 1, there are two factors added, namely TRUST and

HABIT, which might affect customer loyalty. There will be SEVEN SECTIONS in the final

questionnaire (Table 3.10), including:

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Section Number of

factors/questi

ons

Name of factors Number of

variables

Section 1: Supermarket

shopping behavior

20 questions These questions are going to explore the

shopping behavior of supermarket

consumers and their viewpoints about

many factors related to loyalty.

Section 2: Customers’

response

3 factors Customer perceived value 6

Customer satisfaction 5

Customer loyalty 5

Section 3: Perception of

Quality

5 factors In-store logistics 7

Service quality 6

E-service quality 10

Product quality 4

Price 3


Customer Service

3 factors Customer service 10

Customer experience 4

Retail brand experience 6


supermarket image

3 factors Store image 7

Corporate image 3

Corporate social

responsibility

6

Section 6: Other features of

supermarkets

7 factors TRUST 4

HABIT 3

Store accessibility 3

Alternative attractiveness 4

Switching costs 6

Loyalty programs 6

Promotion effects 3

TOTAL VARIABLES 111

Section 7: Demographic

information

8 questions These questions are going to investigate

demographic information

Table 3.10: Final questionnaire’s structure

Respondents were asked to register their choices at each question in the questionnaire, a

majority of the questionnaire being single option questions. However, there are still some

questions allowing respondents more than one option. According to Bourque and Clark

(1994) and Saunders et al. (2016), researchers might do one of the things below when

designing individual questions, including: adopt questions used in other questionnaires, adapt

questions used in other questionnaires, and develop their own questions. It depends on the

research nature and its objectives as well as needed available questionnaires. There are many

types of questions which could be considered, such as: open questions, list questions,

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category questions, ranking questions, rating questions, quantity questions, matrix questions

and combining rating questions into scales (Saunders et al., 2016). The questionnaire in this

research combined many of the above listed types of questions in order to explore and

measure factors which might affect customer loyalty. In particular, rating questions mostly

frequently utilise the Likert-style rating in which the respondent is asked how strong she or

he agrees or disagrees with a statement or series of statements (Saunders et al., 2016:457).

There is no consensus about how many points should be used in a Likert scale. Regarding

statements which were used to measure factors from Section 2 to Section 7, matrix questions

are applied, participants were asked to indicate on a five-point Likert scale whether they

agreed or disagreed with a series of statements (where 1 means “completely disagree” , 2

means “disagree”, 3 means “neutral”, 4 means “agree”, 5 means “completely agree”).

In order to create good-quality findings, the questionnaire created should be reliable, up-

to-date and fit the research objectives. The wording of each question requires careful

consideration to ensure that the responses are valid. “The questions will need to be checked

within the context for which they were written rather than in abstract to ensure they are not

misread and that they do not encourage a particular answer” (Saunders et al., 2016:462).

Besides other questions from section 1 and section 7, from section 2 to section 6, the

researcher has built many statements (variables) which can be used to measure the factors.

All of these statements have been applied to test related factors by many famous academic

researchers. Six statements used to measure customer perceived value are adapted from

Chang and Wang (2011). The abbreviation form can be noted as “6-customer perceived

value-Chang and Wang (2011)”. Applying the same process to other factors, the results will

be presented as follows:

1. 6-customer perceived value-Chang and Wang (2011) and Eggert and Helm (2000)

2. 5-customer satisfaction- Kitapci (2013), Lin (2014), El-Adly (2016), Bouzaabia

(2013)

3. 5-customer loyalty- Swoboda (2013), Srivastava (2016), Lin (2014), Terblanche

(2018), Oliver (1997), El-Adly (2016)

4. 7-in-store-logistics- Bouzaabia (2013)

5. 6- service quality- Liu et al. (2011), Jiang et al. (2018)

6. 10- e-service quailty- Zemblyte (2015)

7. 4-product quality- Jiang et al. (2018)

8. 3-price- Jiang et al. (2018), Emi Moriuchi (2016)

9. 10- customer service-Kursunluoglu (2014)

10. 4-customer experience- Srivastava (2016)

11. 6-retail brand experience-Khan and Rahman (2016)

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12. 7-store image- Bouzaabia (2013), Jiang et al. (2018)

13. 3-corporate image- Calvo (2015)

14. 6-corporate social responsibility- Perez (2015)

15. 4-trust- Lombart (2014)

16. 3-habit- Olsen (2013)

17. 3-store accessibility- Swoboda (2013)

18. 4-alternative attractiveness- Calvo (2015), Tung (2011)

19. 6-switching costs- Tung (2011), Qui et al. (2015), Liu et al. (2011)

20. 6-loyalty programs- Stathopoulou (2016)

21. 3-promotion effects- Emi Moriuchi (2016), Tung (2011)

(Appendix 3.4 demonstrates questionnaire survey of this phase and Appendix 3.5

presents where the statements which are used to measure the researched factors come from

and code book for other questions used in questionnaire).

All items in the questionnaire created in this research were adapted from published

works that relate to the research topic.

In this phase, translation and back translation which was mentioned in section 3.7.3.3

will also be applied before conducting the survey.

3.9.6. Data collection

This research utilised quantitative surveys for data collection. This method was used

because of its nature fitting the positivist perspective as explained. Saunders et al. (2016)

present many types of questionnaire which are drawn as follows; in this step, self-completed

postal (mail) questionnaires, where the questionnaire was posted to respondents who return

them by post after completion and delivery and collection questionnaire, where the

questionnaire was delivered by hand to each respondent and collected later. Other survey

alternatives including internet questionnaire (web questionnaire and mobile questionnaire),

interviewer-completed (telephone questionnaire and face-to-face questionnaire) (Saunders et

al., 2016) were not selected due to time and cost constraints. In addition, it might take

respondents 15-20 minutes to complete the whole questionnaire, other survey alternatives as

presented above seem to be impossible to deploy.

Due to a large number of data which needs to be collected, postal or mail questionnaires

enable researchers access to large groups of supermarket consumers easily with wide

geographic coverage at relatively low cost. The preferred data collection approach in this case

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is getting the hard-copy of the survey in order to facilitate data input later. The issues can be

noted in Phase Two as follows: response rate might not be high due to consumers being

unwilling to answer the survey or being biased by other factors. According to Saunders et al.

(2016), response rate in this method is normally 30% to 50%, the answers from respondents

might be contaminated by consultation with others or in some cases, it being impossible to

determine that targed respondents have actually generated the replies received. The final

issue can be invalid answers or mistakes occurring in replies because some consumers might

not answer all questions or some of them might automatically tick the same box for all

multiple-choice questions. In order to avoid low response rate, when sending the

questionnaire, the researcher had used a professional cover letter from Hull University to

explain the purposes of the research and its expected meaningful contribution. In addition, the

researcher stated clearly in her personalised cover letter that all return postage would be free

of charge. In other words, respondents would not be charged with paying the fee. In addition

before doing surveys at the supermarkets, the researcher might encounter difficulties in

obtaining supermarkets’ permission for conducting surveys at their premises.

Besides that, the researcher asked every single friend currently working at different

companies in Vietnam for their help in completing at least 20 questionnaires by sending

copies to their colleagues and returning them once completed. There are 300 questionnaires

expected to be completed in this way at each targeted city (20*15, 15 is the number of people

being asked for this support). In total, it could be expected to get 300*5=1500 completed

questionnaires if the response rate was high. Thanks to 5 year-experience in teaching, the

researcher has a good relationship with some big companies who have supported students to

develop their practical skills. Therefore, these resources might be used. As a lecturer, the

reseacher can easily access another source: students, who are also supermarket consumers.

Besides that, going to supermarkets and conducting a survey in order to access other groups

of consumers is also a possible choice but it costs time and money.

The steps of data collection and data analysis can be summarised as follows (Figure

3.11). The time period for data collection of PHASE TWO was from 16 March to 28 July

2018. The researcher used many possible ways to get the questionnaire completed by

respondents by sending the questionnaires directly and indirectly to respondents and

travelling to the five different cities to deploy her data collection strategy. There are 8 steps in

this data collection process:

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1. Develop a questionnaire

protocol

2. Back translation

4. Check sample frame and

contact for surveys

3. Pilot survey

6. Follow up and remind the

deadline

5. Professional letter and

questionnaire will be sent to

respondents based on their

preferable channel

7. Collecting questionnaires from

differences sources, input data

and coding

8. Data analysis

Questionnaire will be created based on previous literature

review, the research objectives and some new factors

revealed after Phase 1 if needed.

Back translation and cross-checking will be applied in order

to improve the accuracy and reliability level.

10 pilot surveys should be done in this step to check

understanding, jargon or language on the provided

Vietnamese version.

Checking the list of potential respondents and contact for

surveys

Sending all of supported documents and the questionnaire to

respondents

Following up and sending the reminder for deadline

Gathering questionnaires from different sources, inputting

data to Excel, coding and input the whole data to SPSS

e file to SPSS

EFA/CFA/SEM

Figure 3.11: Data collection process applied in Phase Three

Source: Adapted from Churchill and Lacobucci (2010)

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Figure 3.12: Types of questionnaire (Saunders et al., 2016:440)


For quantitative data, this section generally demonstrates the tests undertaken. First of

all, descriptive statistics which relate to data frequencies, means, and standard deviations will

be presented. Exploratory factor analysis (EFA) is used to examine the data sets from the

questionnaire and explore any latent constructs, remove duplicated variables, determine

underlying dimensions or factors which are not known a priori in a set of correlated variables

(Hair et at., 2011). Confirmatory factor analysis (CFA) and structural equation modelling

(SEM) will be used in this research to determine the validity, reliability and relationships

between many remaining variables after EFA. There are two main approaches to estimate the

relationships in a structural equation model (Hair et al., 2010), including covariance-based

SEM (CB-SEM) and variance-based partial least squares SEM (PLS-SEM) approach. “PLS-

SEM is the preferred method when the research objective is theory development and

explanation of variance (prediction of the constructs” (Hair et al., 2014:14), PLS-SEM works

effectively with small sample sizes and PLS-SEM can not be applied when structural models

content circular relationships between the latent variables (in this case, customer perceived

value, customer satisfaction and customer loyalty are dependent variables and their inter-

relationship will be investigated). However, CB-SEM can resolve the above limitations as

this research is expected to collect more than about 2500 questionaires in order to compare

between strategic groups (111 variables and many strategic groups in the retail industry),

therefore, CB-SEM will be chosen. An analysis of CB-SEM is also used in this research in

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order to demonstrate the relationships between many variables using regression and

covariance among latent constructs or variables (Grant, 2003; Hair et al., 2011). These

analyses will be presented in Chapter 5-6. The AMOS program will be used to run the data

because AMOS Graphic (which is a part of AMOS software), can help to formulate a

publication-quality path diagram quickly, it can be more comfortable for researchers to work

within graphical interface rather than a more traditional programming interface (Byrne,

2010). Chang et al. (2016) and Jarvis et al. (2003) analysed and discussed the difference

between formative and reflective measures, and how they were handled in SEM; the key

difference between these two measures is the direction of the “causal” arrow in a conceptual

framework which shows whether a construct indicates manifest variables (formative) or vice-

versa (reflective). In this research, with all constructs, covariation among the measures is

caused by, and therefore reflects, variation in underlying latent factors. In other words, the

direction of causality is from a construct to the indicators, changes in constructs are

hypothesized to cause changes in the indicators (Jarvis et al., 2003). Therefore, a measure of

these constructs in this research is referred to as a reflective and it is shown in Figure 6.1 and

Appendix 6.4.

3.9.7.1. Exploratory factor analysis

“Factor analysis provides the tools for analysing the structure of the interrelationship

(correlation) among a large number of variables by defining sets of variables that are highly

intercorrelated, known as factor (Hair et al., 2010:94). The next step of EFA should be CFA

(confirmation factor analysis). EFA is considered as a data reduction method (Pallant, 2017).

The critical assumptions of factor analysis

Firstly, Hair et al. (2010) recommend that in order to use EFA, the minimum sample size

should be 50 observations and a desired ratio of 5 observations per variable is needed.

Secondly, the statistically significant Barlett’s test of sphericity with sig.<.05 which indicates

that sufficient correlations exist among variables should be applied, followed by checking the

index of KMO (Kaiser-Meyer-Olkin) measure of sampling adequacy. The KMO should be

higher than 0.5, according to Hair et al. (2010), KMO values between 0.5 to 0.7 are

acceptable, higher than 0.7 is great. In this research, all variables after internal consistency

(reliability and correlation) step will be used for EFA.

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Factor analysis related issues

There are many analysis and rotation methods used in EFA, due to the nature of the

research that conducting CFA after EFA, a principal axis factoring and Promax rotation will

be used. There are some criteria in this step: factors with eigenvalues should be greater than

1, the extraction sums of squared loadings (cumulative) should be higher than 60%. In

addition, all factor loading coefficients need to be greater than 0.5 and that no factor-cross

loading occurred is also needed.

3.9.7.2. Confirmatory factor analysis

CFA related to reliability, convergent and discriminant validity testing, the detail criteria

will be presented at chapter 6 (section 6.3).

3.9.7.3. Structural Equation Modeling_Goodness of fit

The chi-square (2) GOF is used to investigate the differences between the observed

and estimated covariance matrices (Hair et al., 2010); it is calculated as follows:

2 = (N-1) (observed sample covariance matrix-SEM estimated covariance matrix)

In that, N is the overall sample size. “As the sample size increases, power increases and

the chi-square test can return a statistically significant outcome even when the model fits the

data reasonably well. The null hypothesis is “no difference in the two covariance matrices”.

The expected situation is no difference between the two matrices. If the chi-square >0.5, the

null hypothesis will be accepted. An option to balance against large sample sizes driving

statistical significance is to divide the chi-square value by the degrees of freedom (df) in the

analysis” (Meyers et al., 2013:870). This figure is called the normed chi-square or chi-square

ratio (2/df), if

2/df is less than 2, the model is considered as a good fit (Byrne, 1989), if it is

from 2 to 5, the model is considered as an acceptable fit (Marsh and Hocevar, 1985). The

smaller index indicates better-fitting models. However, according to Hair et al. (2010:667),

“the statistical test or resulting p-value is less meaningful as sample sizes become large or the

number of observed variables becomes large”. Therefore, considering another index is

necessary.

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Absolute fit indices

“Absolute fit measures indicate how well the proposed interrelationships between the

variables match the interrelationship between the actual or observed interrelationships”

(Meyers et al., 2013:870). The five most common absolute fit indices are the chi-square, the

chi-square divided by the degrees of freedom test (as presented above), the goodness-of-fit

index (GFI), the root mean square error of approximation (RMSEA), the root mean square

residual (RMSR).

The goodness-of-fit index (GFI) demonstrates the proportion of variance in the sample

correlation/covariance accounted for by the predicted model, with the value range between 0

(no fit) to 1 (a perfect fit), it means that GFI explain how well a currently proposed theory fit

the sample data, that GFI is equal or higher than 0.9 will be considered as an acceptable

model (Hair et al., 2010; Tabachnick and Fidell, 2007).

The root mean square error of approximation (RMSEA) is “the average of the residuals

between the observed correlation/covariance from the sample and the expected model

estimated for the population” (Meyer et al., 2003:871), it presents how well the proposed

model fits a whole population. An acceptable value of RMSEA is between 0.05 and 0.08

(MacCallum et al., 1996). “Lower RMSEA values indicate better fit” (Hair et al., 2010:667)

The root mean square residual (RMR) and standardised root mean residual (SRMR):

RMR is “a measure of the average size of the residuals between actual covariance and the

proposed model covariance” (Meyer et al., 2003:871). MacCallum et al. (2009) indicated that

SRMR demonstrates how closely the model fits the correlations among the measured

variables. “A rule of thumb is that an SRMR over 0.1 suggests a problem with fit”. Therefore,

the smaller the RMSR, the better the fit with a target value 0.05 or less (Hair et al.,

2010:668).

Relative fit indices

Relative fit measures are also known as “comparisons with baseline measures or

incremental fit measure. It indicates the relative position on this continuum between worst fit

to perfect fit, with values greater than 0.9 suggesting an acceptable model fit between the

model and the data” (Meyer et al., 2013:871). Common relative fit measures are the

comparative fit index (CFI) which compares a model to the data, the normed fit index (NFI),

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the incremental fit index (IFI), the Tucker-Lewis index (TLI) which compares a proposed

model’s fit to a null model. All these indices should be equal or higher than 0.9 (Byrne, 2010;

Knight et al., 1994, Hair et al., 2010)

Parsimonious fit measures

Parsimonious fit measures are sometimes called “adjusted fit measures”, it is used to

adjust for an inflated fit bias. “Parsimonious fit measures have no generally accepted

cutoff…It is recommended to compare two competing models, and the model with the higher

parsimonious fit measure should be judged as superior” (Meyer et al., 2013:872). Common

parsimonious fit measures are the adjusted GFI (AGFI) and the parsimonious GFI (PGFI), the

parsimonious NFI (PNFI). The model with AGFI and PGFI equal or higher than 0.9 can be

seen as an acceptable fit (Kelloway, 1998) and ideally, that PNFI is equal or greater than 0.5

indicates an acceptable model (Mulaik et al., 1989). The following table (Table 3.11) will

summarise the criteria of a goodness-of-fit indices mentioned above:

Type of model

fit indices

Model fit indices Recommended

value

References

Absolute fit

indices

Chi-square 2 >0.05 Hair et. Al (2010)

Chi-square ratio 2/df < 2 Byrne (1989)

Goodness-of-fit index GFI ≥ 0.9 Hair et al. (2010), Tabachnick and

Fidell, (2007)

Root mean square error of approximation RMSEA 0.05-0.08 MacCallum et al. (1996)

The standardised root mean residual SRMR ≤ 0.08 MacCallum et al. (2009)

Relative fit

indices

Comparative fit index CFI ≥ 0.9 Byrne (2010); Knight et al. (1994),

Hair et al. (2010), Garver and

Mentzer (1999)

Normed fit index NFI ≥ 0.9

Incremental fit index IFI ≥ 0.9

Tucker-Lewis index TLI ≥ 0.9

Parsimonious

fit indices

Adjusted GFI index AGFI ≥0.9 Kelloway (1998), Hair et al (2010)

Parsimonious GFI index PGFI ≥0.9 Kelloway (1998)

Parsimonious NFI index PNF ≥ 0.5 Mulaik et al. (1989)

Table 3.11: The criteria of a goodness-of-fit indices for the measurement model validity

Garver and Mentzert (1999) suggested three ideal GOF indices, including RMSEA, CFI

and TLI. According to Hair et al. (2010) and Garver and Mentzert (1999), there are three

measures to improve the model fit. Firstly, checking factor loadings at standardised

regression weight, that the values are equal or greater than 0.5 would be considered as

acceptable values. In the case of the values lower than 0.5, the items should be removed from

the data set and the analysis rerun. Secondly, standardised residuals (SRs): the large residual

value strongly affects the model fit, if any variable demonstrates an SRs value greater than 2

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it should be removed from the dataset. Lastly, the model fit can be improved by modification

indices. The lower chi-square, the fitter model, each MI value illustrates the expected change

in chi-square and the expected parameter estimate. MI can suggest which items should be

connected first to improve the chi-square index. The higher MI should be prioritised for

modification first (Garver and Mentzer, 1999) and then the model should be re-calculated.

3.10. Conclusion

This chapter has presented the research methodology applied by highlighting differences

between philosophical stances and paradigms, ethical paradigms, then indicating the applied

philosophy, paradigm and ethical stance for this research. In addition, the chapter also

indicates how the research will be conducted by demonstrating research design, research

process and research method for two phases. The next chapter is going to analyse the

qualitative data collected from expert and supermarket’s consumer interviewing.

The following figure (Figure 3.R) will briefly demonstrate results from two phases:

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Figure 3.R: Main results from two phases

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Chapter 4: Phase One - Qualitative data analysis

This chapter will analyse the data collected from interviewing both experts and

supermarkets’ consumers. Based on the research objectives, the researcher should achieve

dividing Vietnamese supermarkets into different strategics in order to investigate differences

between groups regarding factors affecting customer loyalty. Therefore, interviewing experts

is essential; section 4.1 will provide analysis for expert interviewing which includes strategic-

group mapping as well as the current competitive environment of the Vietnamese retail

industry. In the literature review, all possible factors influencing customer perceived value,

customer satisfaction and customer loyalty have been presented; however, due to a different

industry life cycle, culture as well as customer behavior, interviewing Vietnamese

supermarkets’ consumers should be conducted in order to find whether there are other factors

affecting customer perceived value, customer satisfaction and customer loyalty that have not

been explored in this section of the review. In addition, this process will be beneficial for the

quantitative research later in this research. If any other new factors are found, they will be

added to questionaires and measurable variables for these constructs will be built before

conducting surveys. In section 4.2, there are 35 questions asked during customer inteviewing,

analysis of which is necessary and will support the researcher to explain the quantitative

results thoroughly.

4.1. Step One - Analysis for expert interviewing: Strategic group mapping

4.1.1. Introduction

Data collection method for this phase was presented at section 3.8; this part is going to

analyse the collected data from expert interviewing, followed by discussion, then, ended

with some considerations after expert interviewing.

4.1.2. Expert’s information

After contacting specialists, only one expert is available for interviewing. Although the

sample size is small with one participant, the quality of research and interview as well as the

information collected can be considered as high because this expert has been listed in the top

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specialists in strategy in Vietnam. Besides that, with one hour and thirty-minute interview,

the desired information was succesfully collected.

The expert is Xuan Lan Pham, he is currently working at the university of Economics Ho

Chi Minh City, with 40 years-experience at both academic and business circle, he is well-

known as a top retailing and strategy expert in Vietnam. He has done much research related

to customer satisfaction, customer loyalty and business strategy.

The answers below are re-written by the researcher based on the information collected

from expert’s comments.

4.1.3. Data analysis and discussion

PHASE1_Q1_Participants were asked to give a brief review about the overall situation

of the Vietnamese retail industry. Besides that, the interviewer asked about the current

role of traditional markets in Vietnam and how cultural factors affect consumer

behavior. The interviewees are free to present his/her viewpoints.

The following information was collected from the Vietnamese retailing and strategy

expert. He presented his views on the overall situation in the Vietnamese retail industry. In

Vietnam, supermarkets have impressed with large realignment from being regarded as

unprofessional to professional and have reached international standards about how

supermarkets should be formed and served. Supermarkets used to sell some normal consumer

products with average quality. However, they have covered different kinds of grocery items

and diversified their categories, serving different segments with large scale and being

rewarded by building retail brand names in the long-term. In the past decade, the incredible

development of retailing formats and competition between firms in order to gain market share

have led to a colourful and varied retailing landscape. In particular, the market is currently

undergoing many mergers and accquisition activities between firms, and fierce competition

with the entry of many strong foreign retailers. The traditional market itself has a certain role

in the Vietnamese community, due to the fierce competition from other retailing formats, the

traditional markets have gradually changed the way they work in the big cities with more

civilization, and they have arranged their activities, as well as selling many items associated

with the traditional consumption culture of Vietnamese people. Besides that, as a result of

globalisation, many people have been changing their consumption styles and begun to prefer

products with foreign brand names. The population is also getting used to the term “fast

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food”. In general, many retail stores have established complex formats serving consumers not

only with grocery products but also fresh food, entertainment, fashion and so forth, followed

by the integration of advertising and media industries with names such as Cresent Mall, Aeon

Mall, Vivo City and so forth… Most of them have a modern and professional look, and enjoy

comprehensively professional logistics services.

PHASE 1_Q2: Participants were asked to give their viewpoints about the current

situation of the supermarket sector as well as the competitive environment in Vietnam.

Vietnamese supermarkets have been developed through three stages. At the first phase,

supermarkets served many main daily consumption needs such as flip-flops, household

utensils, pet food, flowers, electronic items, food, grocery products, bakery, clothing,

television and furniture. Typically, Maximax, Coopmart and BigC supermarket, they all still

have a certain position and some of them are holding court and becoming leaders with huge

market share in the consumer goods market. They can be considered as enjoying similar

popularity to that of Walmart in the United State. The second stage has marked the

emergence of specialised supermarkets with specific products or functions, with many

wholesale formats being established and indirectly competing with supermarkets in the first

stage (Metro or Aeon). The third stage (for about the last six or seven years) is the current

situation where supermarkets are serving the multi-segments such as daily food, groceries,

entertainment and its services, drugstores, beauty parlours, barber shop, fashion and so forth.

These formats have attracted consumers from different groups, especially at the weekend,

when people enjoy a day shopping and using the other comprehensive services offered

nearby. With this format, supermarkets have integrated with many other retailers, alliances

with famous-drink and food brand names, pulling other retail groups to operate in the same

areas in order to cross-serve their consumers. It can be said that “everything people need to

enjoy their days, they have it in here”. The idea of gathering possible services needed by

consumers in the same place is a great improvement in the Vietnamese retailing industry.

There are many services and products offered for children as well, such as ground play,

English centres for both children and adults. This also is a reason that retailers can attract

more familyconsumer groups. Besides that, some banks have located in this supermarket

format as well in order to facilitate their customers during the shopping process or other

personal requirements. Accordingly, the advertising industry also follows and penetrates to

these multi-purpose supermarkets. The whole integrated provision of services has led to

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greater efficiency of the supermarkets which can replace other supermarket formats in the

future. However, compared to the UK supermarkets, other integrated establishments such as

gas stations, car washes, bill-paying service and repair shops have not appeared in Vietnam.

Regarding the competitive environment, strong and full development is the current

nature of Vietnamese supermarkets in the last five years. With the supermarket format,

strategic groups are clearly separated but the development is still not synchronised.

Differences and variety of functions are also a factor that can facilitate grouping a client-

group flow. For instance, with daily shopping for groceries, Vietnamese consumers usually

choose Coopmart and Big C; shopping with entertainment services, consumers choose a

multi-functional supermarket. Besides that, wholesale supermarkets are still competing with

other strategic groups to some extent, the main competitive point is to focus on selling

foreign products and specialised items with large quantities, and in return consumers can

enjoy reasonable prices. The level of competition and attractiveness between strategic groups

is different. Therefore, competitive forces at each strategic group will be different. However,

the summarised analysis that follows can demonstrate a five forces review affecting the

retailing industry: consumers have a high power; suppliers have a low power compared to

supermarkets themselves; and there is a significant threat of substitution; the Vietnamese

retail market is identified as fragmented, competition is high; the threat of new entrants is

high (full explanation was presented in section 2.3.3.2).

Besides that, there is competition between different strategic groups and within groups,

groups located near each other in the strategic group map usually attract more consumers

from other groups by using marketing with good promotion and services offered,

concentrating on specilised products. For instance, that Lotte and Aeon offer multi-functional

products and services leads other supermakets to mimic these improvements and apply to

their business model. Therefore, fierce and ceaseless competition between supermarkets is

happening. The term “ecosystem-strategic supermarkets” or “Supermarket Ecosystem” can

be used in this situation. In that, supermarkets are much more than large grocery stores, they

also offer various business integrations and are operating as commercial centres. Services

offered attached to supermarkets have been considered as one of the main factors that can

attract more consumers. This business format has been becoming very popular in Vietnam.

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PHASE1_Q3: Participants were asked for their opinion of techniques that can be used

to group firms into their right strategic groups

That checking similar points between supermarkets in many ways such as from the

products and services offered, degree of specilisation, company structure, prices, targeted

segmentations, firms’ size, brand name building, expanding strategies, the ways of

competition or alliance and so forth can facilitate strategic group mapping process. The main

technique should follow Porter’s guide (1980) which was presented in section 2.1.3.2.

PHASE1_Q4: Participants were asked to group the 12 main Vietnamese supermarkets

to their right strategic groups. The interviewer showed the list of supermarkets (Table

2.3.1). The respondents were also asked the reasons for their choices.

There are 12 main supermarkets in Vietnam, located across the country (Table 2.3.1).

Based on the technique suggested by Porter (1980), Vietnamese supermarkets can be grouped

into five different strategic groups, based on recommendation from an expert in retailing from

Vietnam, as follow:

1. GROUP 1: Group of specilised daily consumer goods: firms in this group have

covered a wide geographical area across the country, the business focus to serve

consumers with their basic daily consumption of food, grocery products, household

utensils. Typical of this group is Coopmart and BigC.

2. GROUP 2: Group of Multipurpose premium supermarkets1: operating under

ecosystem-strategic format but choose to locate at prime locations and luxury areas,

focus on a group of rich people living at newly created cities, luxury apartments,

especially concentrating only on retail sales rather than wholesale. Typical of this

group is Lotte.

3. GROUP 3: Premium supermarket chains with convenience stores: the

characteristics of this group are high quality products such as fresh meats and organic

vegetables without chemical pesticides; products with clear origin, especially fruits.

They also offer daily consumer goods but with premium quality and cover a huge

geographical area in a main city with flexible stores allocated, especially, a majority

of their customers being people who live in new urban segments and areas. Besides

that, they have expanded markets with a huge amount of convenience stores in urban

areas in order to attract more customers, compared to GROUP 1, GROUP 3 is

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considered as a “premium” group with premium price charging. Typical of this group

is Vinmart.

4. GROUP 4: Group of Multipurpose supermarkets 2: operating under ecosystem-

strategic format including Aeon mall, Vivo city, Cresent mall or wholesale format as

Metro. These groups often locate in crowded areas but far away from the central area.

5. GROUP 5: Other supermarkets

It can be noted that “ecosystem supermarkets or malls” in Vietnam might be different

from the concept in western areas, malls in Vietnam are characterised by a form of large

battlefield. Many stalls and areas in the whole supermarkets or a mall are not owned by

supermarket owners. They are from different small retailers who sign a partnership contract

or even just rent a space for their business. There is a good linkage between many retailers;

they compete with each other or even with supermarkets themselves. Besides that, when

supermarkets integrate with other attached businesses, they create a favourable business

environment to avoid fierce competition. For example, at the food court, there is a limitation

on the number of country-specific restaurants and variety of choices of food from different

countries. These stores will be asked to move out if they cannot achive a business with good

profits. In another scenario, the supermarket owner will give a chance for potential and good

firms moving in. In general, the decision of which firms can move in and integrate with the

supermarket business is very selective. Supermarkets itself have more power than other small

retailers and always choose “win-win” strategies. The mall and multifunctional supermarkets

also compete fiercely and threaten to take over market share from other strategic groups; the

form of ecosystem in supermarkets is significantly successful in Vietnam.

PHASE1_Q5: Participants were asked to present which possible factors might affect

customer loyalty based on their profession.

Besides many factors presented at literature part, “the customer-oriented business model”

should be considered. In many cases, customers tend to be loyal to supermarkets because they

are happy with a specific business model. For example, consumers can claim that they are

loyal to multi-functional supermarkets because “everything they need, it will be fulfilled

there”

PHASE1_Q6: Participants were asked to present the linkage between customer

perceived value, customer satisfaction and customer loyalty.

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There is a certain linkage between customer perceived value, customer satisfaction and

customer loyalty. However, it depends on the situation and individual perceived value, the

linkage level might be different. These differences will be tested and discussed in Chapter 6

and 7.

4.1.4. Conclusion

Many main points collected from the expert interview, including the current situation in

the Vietnamese retail industry, and specifically the supermarket sector; the comments on

competitive business environment; the suggested techniques to group firms to strategic

groups, then appling these techniques in practice, the case in Vietnamese supermarket sector.

Via this interview, the brief picture about the Vietnamese retailing industry, particularly the

supermarket sector was presented. In the end, the expert commented, noticed and dicussed

some futher factors which might affect customer loyalty, apart from the one presented at the

literature review part.

4.1.5. Summary

This section investigated the strategic groups in the Vietnamese supermarket sector.

From the beginning, data collection method that expert interviewing was mainly used had

been indicated, after interviewing, data analysis and discussion parts were presented with the

result and clear explanation why the Vietnamese supermarket firms have been placed in their

specific strategic groups.

4.2. Step two - Analysis for consumer interviewing: Customer loyalty perception

4.2.1. Introduction

This section aims to explore the customer loyalty perception or behaviour of customers

from the Vietnamese supermarket and traditional retail channels. Data collection method was

introduced in section 3.8. This section is going to analyse and discuss the collected data.

4.2.2. Details of Interviewees (supermarket consumers)

As mentioned in section 3.8.1, about 20 interviews should be conducted. However, in the

process of contacting the interviewees, some of them responded lately and confirmed whether

they could attend the interview or not. In the end, there were 21 interviews being

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implemented. Details of all interviewees are presented in Table 4.1. The rule of coding

interviewees can be described as follows: HCM for “Ho Chi Minh”, CT for “Can Tho”, BD

for “Binh Duong”, HN for “Hanoi”, DN for “Da Nang” - this information explains where

consumers are currently living (locations); a number after a location illustrate the number of

consumers interviewed in that location; M and F in a code demonstrates “male” and “female”

respectively; the two numbers after M or F present interviewees’ ages. Besides that, time,

date as well as collection method, recording status is also reported in Table 4.1. That

respondents have a different demographic information and stay at different areas will

contribute to create a more reliable result.

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Interviewee’s

code

Time Date Collection

method

1 HCM1_M60 19:00-20:00 11/03/2018 Face-to-face No recorded

2 HCM2_M27 11:10-11:50 12/03/2018 Online via Skype No recorded

3 HCM3_F35 12:00-13:00 12/03/2018 Face-to-face Recorded

4 HCM4_F45 17:15-18:00 13/03/2018 Online via Skype Recorded

5 HCM5_F60 19:00-20:00 13/03/2018 Face-to-face Recorded

6 HCM6_F33 10:30- 11:00 14-15/03/2018 Online via Skype Recorded

7 CT1_M27 9:45-10:45 13/03/2018 Online via Skype Recorded

8 CT2_F35 15:00-16:00 14/03/2018 Online via Skype Recorded

9 CT3_M53 11:00-12:00 15/03/2018 Online via Skype Recorded

10 BD1_F31 14:00-15:00 16/03/2018 Face-to-face No recorded

11 BD2_F30 22:00-23:00 12/03/2018 Online via Skype Recorded

12 BD3_F26 16:00-17:00 16/03/2018 Face-to-face No recorded

13 HN1_F24 22:00-23:00 13/03/2018 Online via Skype Recorded


15 HN3_M24 14:00-15:00 12/03/2018 Online via Skype Recorded

16 HN4_F26 12:30-13:30 12/03/2018 Phone call No recorded


18 DN1_F24 15:00-16:00 13/03/2018 Online via Skype Recorded

19 DN2_F35 10:00-11:00 14/03/2018 Online via Skype Recorded

20 DN3_M18 10:00-11:00 17/03/2018 Online via Skype No recorded

21 DN4_F19 15:00-16:00 17/03/2018 Online via Skype No recorded

Table 4.1: Details of interviewees from Phase One

(supermarket consumers)

Some descriptive information about interviewees will be briefly summarsied as follow

(Table 4.2):

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LOCATION Frequency Percent Notes

Ho Chi Minh 6 28.57%

Southern Can Tho 3 14.29%

Binh Duong 3 14.29%

Ha Noi 5 23.81% Northern

Da Nang 4 19.05% Middle

Total 21 100%

GENDER Frequency Percent

Male 6 28.57%

Female 15 71.43%

Total 21 100%

OCCUPATION Frequency Percent

Students 2 9.52%

Self employment 3 14.29%

Office staffs 5 23.81%

Housewife 8 38.10%

Unemployment 0 0.00%

Other 3 14.29%

Total 21 100%

AGE RANGE Frequency Percent

Under 18 0 0.00%

18-22 2 9.52%

23-30 9 42.86%

31-40 5 23.81%

41-55 2 9.52%

Above 55 3 14.29%

Total 21 100%

EDUCATION LEVEL Frequency Percent

Under high school 1 4.76%

Under college 4 19.05%

College, undergraduate 16 76.19%

Total 21 100%

Table 4.2: Interviewees’ descriptive information

4.2.3. Data analysis and discussion

There were 21 respondents who are supermarket consumers in this phase, they are from

different locations in Vietnam and different age ranges, interviewees’ information was

presented in detail in section 3.9.1. There were 35 questions in the interview, all questions

were coded with the structure “P2_Qi”, for example, P2_Q1 means “Phase 2 and question 1”,

i means the question’s numbers (see appendix 4.1 for full used questionnaires). The full

results will be presented as follow:

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With P2_Q1, when asked which supermarkets exist in your cities, all interviewees

named supermarkets located in their areas, such as Coopmart, BigC, Lotte, Vinmart, Aeon,

Metro, Vinatext and Auchan. However, there are some respondents who remain confused

about the terms supermarket, hypermarket, department stores, shopping mall, convenience

stores; they started to name where they have gone for shopping.

With P2_Q2, when asked how often respondents go to supermarkets, there are many

answers which can be divided into 4 groups. The first group includes people who usually go

to supermarkets around twice or three times a week, such as HN5_F56, HCM5_F60,

BD2_F30, HCM4_F45, 100% of the respondents of this group are female and a housewife

which allows them to have more time for shopping at supermarkets. HN5_F56 stated “I have

retired and currently live with my husband, I have a very free and flexible time, so I often go

to a supermarket, three or four times a week, sometimes just looking and going around but

finally, I bought many items. Normally, I go there to buy daily food and keep it in a fridge, I

live in an apartment where supermarkets are just under or near my building”. In this group,

BD2_F30 go to shop at a supermarket every day because she is working in the supermarket.

Another group is going to supermarkets once a week, such as HCM_M60, CT1_27,

HCM6_F33, HN2_F30, HN1_F24, HN3_M24. Depending on the nature of their jobs, some

people go at the weekend with family, some of them go to supermarkets to shop for the whole

family when they are free. In this group, HN1_F24 said “ I usually go to supermarkets with

my mum to buy food or consumption products for family, but I do not really care about

buying consumption stuffs because I have no right to decide which products should I buy and

use, my mum is in charge, for daily foods, she choose traditional markets. For me, I just buy

some skincare products at a supermarket”. Vietnamese family-focused culture has affected

consumption behaviour. Normally, one person in the family will be in charge with daily food

and consumption products, other members in the family tend to eat and use already-bought

products without complaining.

Some respondents go to supermarkets twice a month because of their habits of going to

supermarkets with the whole family and buying many goods which are sufficient for them to

use until next shopping time, such as HN4_26, DN2_F35, HCM3_F35, CT3_M53. The final

group does not usually go to supermarkets, once a month or once every three months, such as

HCM2_M28, CT2_F35, DN1_F24. Some people in this group also stay with a big family,

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they are not in charge of buying grocery products, some of them choose to shop at traditional

markets due to their job nature which always keeps them busy.

With P2_Q3, when asked whether preferring shopping at supermarkets or traditional

markets, a majority of respondents such as HN4_F26, HN1_F24, HCM1_M60, HCM6_F33,

DN1_F24, BD3_F26 chose supermarkets because of advantages such as clean and fresh

atmosphere, trustworthy and diversed goods as well as its types, a variety of delicious and

fresh food, not worrying about bargains because clearly presented prices, good returns

policies, nice and polite attitude of in-store staff, safe household utensils offered, clearly

stated origin, an eye-catchingly display, easy to find, especially, the comfortable feelings of

whether purchasing or not after checking without worrying annoyed anyone. Besides that,

thanks to home-delivery service offered, consumers can buy as much as they want without

thinking about being too heavy to carry home; products from supermarket seem to have a

higher quality compared to the one at traditional markets.

However, there are some consumers preferring shopping at traditional markets such as

CT1_M27, HN3_M24, CT3_M53. They explained some disadvantages of shopping at

supermarkets and reasons why they choose traditional markets. CT1_ M27 said: “I think

shopping at traditional markets is very convenient, it is near my house and I just drive my

scooter to there and get what I want immediately; I do not need to wait for parking or long-

queuing when checking out. Besides that, many fresh vegetables and meats are available

there. Many special home-made products and some kinds of nice fishes are not sold in

supermarkets. However, sometimes I am suspicious about the quality of meats or their

origins, I usually go to specialised meat shops to shop separately. In general, I feel free to

shop at traditional markets, easy to buy and choose”.

With P2_Q4, as mentioning supermarkets, some respondents indicated their most

familiar supermarket brand names but it is not always their loyalty choice. For example,

HCM1_M60 named Lotte as his most familiar, but he is loyal to Coopmart, DN2_F24 named

Vinmart as her most familiar but she is loyal to BigC. They gave a reason for this answer as

some firms have done a good marketing campaign, built a strong brand image as well as

covered all media channels, easy-to-remember slogans. Therefore, they always think about

these brand names when mentioning supermarkets. However, for choosing which one for

shopping and being loyal to, they might need to consider many factors. Other respondents are

loyal to their most familiar supermarkets, HCM5_F60 explained that a mentioned

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supermarket is her top choice because she goes there to shop every day, it is near her area,

she gets used to where the products that she needs are and the supermarket offers an

affordable price. Besides that, she got a loyalty card that allows her to accumulate points

doing any transaction, thanks to an integrated system across the country, she can obtain

points regardless of where products have been bought, this is not the case in other

supermarkets. HN5_F56 is loyal to Vinmart due to many reasons, but she stated she has no

choice, the most important factors affecting her choice is convenience in terms of location, as

she explained, the supermarket is next to her apartment and offers an excellent customer

service. In the case, if closer supermarkets existed, she might move there if all other factors

remained the same. BD3_F26 thinks about Lottemart and always shops there due to its

convenient location and accessibility, the supermarket is near her house and its Korean brand

name gives her a feeling of good quality.

With P2_Q5, most of respondents explaining their main purpose of going to

supermarkets is to buy daily consumption products, some of them are looking for other

service attached in order to relax and spend time with family. Some respondents explained

that they have no time, so buying groceries is their main purpose, if they want to relax, they

might choose a shopping mall with many luxury skin care and household utensils provided, at

the same time, their families still have a choice of different services offered (HN2_F30,

DN2_F35). It can be noted that some consumers going to supermarkets just buy their

intended-to-buy items and finish their shopping quickly, they have no demand for additional

services. HN1_F24 told that she usually goes to a supermarket with her mother when her

mother hears about special discount campaigns at that supermarket.

With P2_Q6, when asked about factors influencing their loyalty to supermarkets and

listing their important factors. It seems to be different between consumers due to their

different education levels, income, and locations. HCM3_F35 mentioned about the

importance of service quality offered, clean toilets provided and origins of products. Other

respondents such as BD1_F18, CT2_F35 mentioned location accessibilities, quality of

products, prices, no scandal occurred, nice corporate image and store image. CT2_F35

mentioned that habit is her top criteria in term of loyalty “BigC is a first supermarket in my

area, I have come there first and bought many products, now I feel very familiar and become

its frequent and loyal customer”. CT3_M53 is loyal to his current chosen supermarket

because of super-friendly well-trained and supportive in-store staffs, nice store atmosphere

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and its convenient location. HN4_F21 did present her impression with customer services

offered by her favourite supermarket “I went there shopping with family, we bought many

products and it was so heavy that we could not carry home, thanks to excellent customer

services, they sent it to my house after we pay 2 hours, it was such amazing service”.

DN2_F35 mentioned about how trust affecting her loyalty “Majority of products I bought

from Metro are traded under foreign brand names, I love and trust foreign products, when I

came there, I was so confident to buy many things”. However, there are a number of

respondents (HN1_F24) presenting that products’ price is the reason why they are loyal to

supermarkets. Therefore, it can be seen that income has affected customer loyalty to some

extent. HN2_F30 who stays in luxury apartments in a new urban area presented that product

quality and convenient location accessibility are the most important factors in her case.

Besides the above factors, HN5_F56 and HCM4_45 also choose Vinmart to be loyal to

because Vinmart has a variety of product ranges and promotion programmes, a premium

price is not a problem for her, she prefers to buy there because of big size supermarket which

allows her to enjoy shopping there. In addition, she is currently a housewife, obtaining points

as conducting any purchase is also here favourite thing. BD3_F26 clearly indicated five top

factors what she considers which supermarkets to be loyal to “For me, there are five main

factors, including convenient location accessibility, clearly stated product origin, attractive

promotion programmes, quick home delivery service, spacious parking area”. DN4_F19

emphasised the importance of in-store staff attitude. She claimed that this is a most crucial

factor if firms want to keep consumers loyal to them, if staff express disrespectful behaviour

and seem not to be supportive, she might move to other retailers even though the original

supermarket satisfies all of her needs. There are some respondents stating that they are not

loyal to a supermarket, they buy products depending on convenience levels, such as

HCM2_M28, HN1_F24. But when asked about their views of factors influencing customer

loyalty, they mentioned price first, convenient location and then customer services.

In general, by using this question, all of the factors presented in the literature review had

been mentioned by all respondents. However, there are two more factors, including TRUST

and HABIT that have been reviewed, the researcher will add these two new factors to her

research framework and be ready for creating scale for future survey (PHASE TWO).

With P2_Q7, considering factors affecting customer satisfaction, a majority of

respondents emphasise the importance of good customer services, friendly well-trained in-

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store staff, product quality, excellent in-store logistics and promotion programmes.

HN3_M24 added “Every single time I go to Aeon supermarkets, their staff bowed low and

gave me a friendly smile, I feel respected”. CT3_M53 considered that price is not the

important factor when considering his satisfaction, in-store logistics should be mentioned.

HCM2_M28, HN5_F60 and DN3_M18 indicate a fresh atmosphere and well-arranged

shelves in stores make them feel good and satisfy. HCM6_F36 explained how customer

services affected their satisfaction. HN5_F56, DN2_F35, HCM4_F45 and HCM3_F35

indicated that product quality is the most important factor to them, they choose and satisfy

with their current supermarket because good quality products are offered. The level of

satisfaction might mainly depend on how well the products provided are in this case. In

addition, many respondents, such as BD3_F26, HCM3_F35, HN2_F30, CT1_M27 presented

that a supermarket brand name and firm image are having a significant influence on them. In

general, when consumers perceive high-value reception when shopping, they will be more

satisfied.

With P2_Q8, respondents started to share their satisfied/unsatisfied experience with the

interviewer, there are many explanations above about how to make consumers satisfied, such

as free and quick home delivery service, friendly staff, nice and free wrapping service, this

section will mainly emphasize an unsatisfied experience. HN2_F30, HN3_M24 felt annoyed

with many things, including long-time waiting for payment, changing the location of product

display, mistaken price or no price or code stated, no supported payment services such as

creating mobile applications that consumers can pay via scanning code. CT1_M27 narrated

that “some shelves are always out of stock, promotional areas look messy, there are no staff

there to tidy up, I feel uncomfortable”. HN1_F24 expressed her unsatisfactory experience

when in-store staff at a supermarket showed their disrespectful and unsupportive behaviour to

her and ignored her question. In conclusion, consumers complain about long-queue waiting

as checkout, no flexible problem solving, and unfriendly staff. DN4_F19 bought an expired

cake because she forgot to check the product’s date when buying, she had supposed that all

products in supermarkets have been checked carefully. She expressed her disappointed

behaviour and clearly stated that she will not come there again. HN4_F26 complained that in-

store staff were not proactively introducing their promotional programmes to her. HN3_M24

complained about supermarkets’ consumers having to pay a parking fee, she said that “I

usually drive my scooter to supermarkets, I feel a bit annoyed when I need to pay a parking

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fee, I bought a lot products there and my money has been kept in my bag which always

locates in the scooter trunk, takes time to get money to pay and feels complicated”.

With P2_Q9, when asked “If you switch to other supermarkets without switching costs

(such as time, finance), would you like to switch?”, 50% of consumers stated that they would

not change, even if the switching cost is zero because they are currently satisfied with their

current supermarkets. Furthermore, a habit is very important to them, they get used to where

needed products are located. The other 50% of respondents explained that they are happy to

change if new established supermarkets are near their house and match their demands. They

all emphasised how important the convenient location accessibility is. Besides that, if there

are new supermarkets built which are far away from their hous compared to the currently

chosen one and many suitable attached services around that area, in the case other factors

match their needs, they will move to the new supermarkets and use other services offered.

For example, even the new supermarkets are slightly far, but it is located near other services

such as spa/ beauty salon, cinema, book stores, consumers might re-consider their choices

and choose new supermarkets.

With P2_Q10, when asked “if you are not satisfied with the service or the quality of the

products at a supermarket, will you be back to visit and shop there again?”, 25% of

respondents answered that they will not stay with a supermarket if they are not satisfied, they

still have a lot of choices, they confessed that their loyalty level is low, they have more power

than the supermarket itself “why I stay there with them if I am not happy, I am happy to pay

more with good quality products and even if it costs me more to go to another supermarket”

(HCM3_F35), “I have no empathy for disrespectful staff and will never shop there again”

(HCM2_M28, HCM4_F45); 75% of respondents said that they will give themselves a second

chance to experience both services offered and product quality, if that unsatisfied experience

still appears, they would like to switch to alternative supermarkets. It all depends on the level

of an unsatisfied experience. For example, BD1_F18 complained about long home delivery

service, but she still keeps shopping at her current supermarket because other factors match

her desire. HN1_F24 narrated about her unsatisfied experience when buying fruit at a

supermarket, it was not as fresh as she expected, she will not try to buy that specific fruit

again but she is still happy with that supermarket. HN5_56 complained about unsupportive

in-store staff attitudes to their manager and got an excuse from them, she felt happy about

that; as she explained that she always gave them a second opportunity.

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With P2_Q11, when asked “how does store image affect your purchasing perceptions

and your satisfaction?”, all of the respondents mentioned in-store decoration and atmosphere

as well as the layout of shelves, the service attitude of in-store staff.

With P2_Q12, when asked “Which kinds of supermarket do you wish to shop? Please

describe?”, besides all of the factors which can make consumers satisfied as presented above

such as free parking service, well-trained and supportive staff, excellent in-store logistics,

good product quality, reasonable price, a variety of products offered, quick checkout services,

many respondents mentioned about their dream supermarkets. HN1_F24, HN2_F30 expected

supermarkets have an electronic board that they can select a wanted product and pay when

driving out, in this way they explained about how they can save their shopping time,

HCM6_F33 also dream about supermarkets applying modern technology where she just

chooses products and the products were sent to her house later. HCM1_60, CT1_M27 expect

that Vietnamese supermarkets have self-checkout service machines. However, the majority of

Vietnamese is still using cash in their daily spending, the self-checkout service machines

cannot be applied unless the number of people using card has been significantly increased.

HN3_M24 recommended that “if consumers who usually buy a lot of products at

supermarkets, they can register an account with a detailed bank card, when they shop, they

will be distributed a small machine which can scan a product barcode and automatically pay

when checking out. It would be perfect” or HCM3_F35 suggested that “Should Vietnamese

supermarkets apply Argos’s business model that using catalogues and electric board to sell

their products”

With P2_Q13, when asked “Does corporate image affect your choice in choosing which

supermarkets to go?”, 100 % of participants said “YES” and they started to explain a reason.

Some respondents considered about where supermarkets’ brand names are coming from,

including domestic and foreign brand name. They demonstrated that foreign supermarkets

give them a reliable feeling. It generates a positive effect in the purchase decision.

With P2_Q14, whether corporate social responsibility (CSR) affects your choice in

choosing which supermarkets to go or not, some respondents said that they will lose trust in

supermarkets which do not have a positive corporate social responsibility, in the case they

have alternative choices, they might move to new supermarkets, if not, they might stay to

shop at that supermarket because “in fact, a negative CSR does not directly affect my choice

as my benefit is still there” CT3_M53 said, HN2_F30 stated that “I will choose to shop there

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if that negative level is low because a supermarket is near my house”. However, she also

added that CSR affects corporate image, that supermarkets contributing to society such as

sponsoring social-cultural events or free events for children will create consumer trust.

Although some consumers do not care about CSR, if supermarkets treat their employees

nicer, employees might be happy and give consumers a better service. Some serious situation

such as business from supermarket seriously affect a natural environment and cause pollution

and damage people’s living environment, all respondents will commit not to shop at that

supermarket anymore. All respondents expressed their disappointed behaviour to firms who

do not pay taxes, but some of them still choose to shop at these supermarkets due to its

indirect effect to them.

With P2_Q15, when asked “Do you think loyalty programmes such as bonus points,

discounts and gifts will affect your decision?”, the majority of the respondents stated that

bonus points or discounts slightly stimulate their purchase decision if product quality remains

unchanged. If other supermarkets which are further from consumers’ houses offer an

attractive promotion, consumers tend to move to that supermarket to experience discounted

shopping but all of the participants supposed that they will not change supermarkets which

they are currently loyal to. In the case, supermarkets offer good promotion programmes, but

their employees show disrespect to consumers or behave in unsupportive ways, respondents

will commit not to go to that supermarket for shopping as well. HCM5_F60 is happy with her

current supermarket when she usually receives free gifts from the supermarket at the end of

each year, even she did reward her points and expressed that she has no desire looking for

alternative supermarkets. In this way, it can be noted that when consumers perceive a high

value offered, they might be satisfied and loyal to supermarkets. However, some respondents

seem to be not really interested in loyalty and promotion programmes, product quality and

how well supermarkets’ employees treat them are the most important factors (HN5_F56,

BD1_F18, DN3_M18 and HCM_F35).

With P2_Q16, when asked “If other supermarkets offer appealling promotions or

discounts, would you be ready to switch to them?”, 100% of the respondents answered “NO”

due to their current choices matching their needs and fitting their situations. Switching and

being committed to a new supermarket takes time and costs. As a result, people are afraid to

change if new benefits provided are low. However, if some expensive products such as

television, washing machine and other electronic devices, consumers might wish to move to a

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discounting supermarket to experience promotion programmes but they will not switch

permanently. In the case, newly-established supermarkets are located near consumers’ areas

and offer an attractive promotion programmes, consumers will give it a go. In Vietnam, there

is a supermarket which commits to their customers that they always offer the lowest price

compared to the same products from other firms, if their clients detect any of their products at

a higher price, clients can give the bills with lower prices offered the supermarket and will

get the voucher of 10,000 VND (32 pence) in return. In this way, this supermarket has

attracted a huge amount of customers at that segmentation.

With P2_Q17, as being given a follow situation “Suppose you are always loyal to

specific supermarket A, if supermarket B opens a store near you or easier for you to get there,

do you wish to switch to shop at supermarket B?”, a majority of the respondents emphasized

that they will give a newly-established supermarket B a try because convenient location

accessibility is also an important factor regarding customer loyalty. However, after

experiencing, if other demanded factors are equal or slightly higher than supermarket A, they

will definitely switch to shop at supermarket B. Some of the respondents chose to open their

choices if the above presented thing happens, they might choose to shop at both supermarkets

depending on how much time they have (HCM4_F45, CT2_F35). CT1_M27 mentioned

about a price factor in this case, he supposed that if supermarket B locates near his house and

offers a slightly higher price compared to supermarket A but other factors are the same, he

will switch to supermarket B.

With P2_Q18, when asked “Do you concern about online service at supermarkets such

as online ordering or home delivery, consulting chat?”. 25% of the respondents expressed

their concerns about online service at supermarkets, they have used the service many times

and have been satisfied with the service provided; this group includes BD2_F30, BD1_F18,

HN4_F26, HCM3_F35, BD3_F26, they explained they were working full-time in an office,

and can save much time by using online services; 50% of the respondents explained that they

are not concerned about the online service due to many reasons related to trust, web interface,

payment method, minimum amount of spending, age range. HCM1_M60, HCM5_60,

HCM4_F45 and CT3_M53 presented their lack of interest in online services. According to

them, they are getting older and due to not experiencing the internet when they were young,

they find difficulty in online buying; 25% of respondents expressed their concerns about

online services, however, they have never experienced the online service offered and will

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consider using it in the future if they can. Besides that, when asked “What do you want from

supermarkets’s online service?”, the group of those who are interested in supermarkets’

online services started to list many expectations such as free and quick home delivery service,

highly-invested web interface, notifying promotion events via email, telephone consultations,

same product quality offered as advertised.

With P2_Q19, when asked “Do you think your favourite supermarkets meet your needs

(products, services?)”, 100% of the respondents said “YES” if regarding daily consumption

products. However, other products such as clothing, cosmetics and specific fruit and meat,

consumers might choose to shop at other favourite stores depending on their demand. For

example, HN5_F56 narrated “I always buy fresh meat at a store which is near my house, they

offer such amazing premium fresh meat that I could not find in supermarket A”. The majority

of participants agreed with the following statement “each consumer has their own needs and

demands, it depends on many factors to decide consumer behaviour as they all are from

different backgrounds, financial status and education levels”.

With P2_Q20, when asked “Do you think the price at this supermarket is reasonable?”,

100% of the respondents said “YES” because that is their choice. Price is not the most

important factor in choosing which supermarkets to shop and be loyal with, it depends on

many other factors. HN2_F30, HCM3_F35, HN4_F26 stated that although being aware of

paying higher prices in their current supermarkets, in return, they believe that the offered

product quality is much higher and other attached services are premium as well. There are

some supermarkets offering cheap prices and amazing deals, but the consumers doubt about

the origin of products and its quality.

With P2_Q21, when asked for commenting about consumer service at the current

chosen supermarkets, consumers expressed their satisfied behaviour as supermarkets provide

a free cash withdrawal machine near the check-out gate and clean toilets inside supermarkets.

However, some consumers complained about a narrow parking space that they could not

easily find spaces for their cars or scooters (BD2_F30), HCM6_F33 expect that supermarkets

should offer playgrounds for children as well, in this way she can enjoy shopping as her

husband looked after children at the playground, BD3_F26 expects that supermarkets in

Vietnam should offer self-checkout machines that those who buy a small amount of product

can check out easily without long-queue waiting and in the case consumers forget their bank

cards, they can pay directly via check out machines after other information authentication is

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provided. HCM3_F35 felt annoyed with consumer service in some cases “I saw that staff at

information unit gather to talk in one place instead of detaching themselves from each other

to consult consumers as needed”.

With P2_Q22, when asked about the feeling when consumers shop at supermarkets,

100% of the respondents illustrated that they feel comfortable, excited and relaxed thanks to

an in-store fresh atmosphere and friendly staffs. HCM3_F35 feel respected and confident

with product origin and quality. Some of the participants feel curious about new products

offered such as childrens games, new taste of products, newly applied modern-technology

games, areas for specific premium foods or products and so forth. However, some male

respondents just feel convenience issue as having a shorter shopping time compared to

female. HCM2_M28 said “I just pop in to buy the products I intended to buy, having no time

for going around, thanks to a convenient location, my transaction finished in 10-20 mins

every single shopping time”. BD2_F30 usually go to premium supermarket, she explained “I

feel the luxury shopping atmosphere here and always be respected”. HCM4_F45 explained

why she did not choose supermarket A because of its cramped shopping space with crowded

people, even if supermarket A offers a lower price. CT2_F35 emphasised the importance of

attached services in supermarkets such as bookstores, good coffee brand names, these things

also are a factor that attracts consumers to go to supermarkets for shopping.

With P2_Q23, when asked their retail brand experience, respondents expressed their

own feelings as follow. CT_F35 considered her current chosen supermarket is a familiar

brand with consumers thanks to its long history, reliable reputation and family-oriented

products provided. BD2_F30 felt a strong impression with her current chosen retail brand

name as this brand name has penetrated the Vietnamese market later compared to others, but

thanks to good quality products and premium attached services offered. In addition, a strong

foreign brand name has also generated trust in consumers’ mind. HN1_F24 mentioned that

free-bus services offered from country areas to a place where her chosen supermarket is

located stimulates shopping and makes consumers feel more respected and more than

welcomed. Therefore, her brand experience is good and she expressed how excited she was to

wait for many beneficial events offered by this brand name. CT1_M27 always feels good

about his current chosen supermarkets as considering their brand name. However, when

sharing about their brand experience, the participants had started to compare and explain why

they choose a specific brand instead of others to be loyal to. The majority of them agreed that

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brand experience affects their choices and behaviour to some extent. For example, when

mentioning the brand name of supermarket A, they feel it is trustworthy, offers premium

services and products, regarding the brand name of supermarket B, they note an affordable

price, cramped stores with not very logical shelves allocated, normal products and services

offered. However, in some cases, consumers still choose supermarket B depending on their

needs and situations. Besides that, wide geographic coverage is also a factor that creates a

good feeling about a retail brand name in consumers’ minds. HN2_F30 has been impressed

about a significantly developed supermarket chain which has expanded to more than 150

stores, including large and medium-size supermarkets and convenience stores after two years

established in Vietnam. When mentioning a brand name experience, logo and brand identity

should be considered; 100% of the respondents admitted that the colour and how the logo of

specific brand name is designed are also considered as the crucial factors to decide the first

impression of consumers about a specific brand. Besides that, DN4_F19 appreciated her

current chosen supermarket where all problems occurred has been quickly solved and staff

are always friendly and supportive. For example, when she complained about too-loud-

broadcast music in a store, a supermarket quickly adjusted the sound and did not forget to

give her an excuse. Therefore, she presented that this supermarket is the best one in Vietnam

thanks to an excellent experience perceived. DN2_F35 did experience many supermarkets

and stated “I used to shop at supermarket X, however, these days, there are a huge number of

products made in China, I doubt about the quality of Chinese products, especially foods,

fruits. I moved to supermarket Y and always think that the brand name of supermarket B

remind me about not good quality products from China”. Therefore, somehow, how good

retail brand experience is has also been affected by in-store products provided.

With P2_Q24, when asked to comment about in-store logistics service of a supermarket

where respondents go to shop, BD2_F30 stated that “It is perfect, thanks to excellent in-store

logistics service provided, I find products easily and quickly, its logically allocated shelves

and adequate products on shelves always make me feel comfortable. Enthusiastic staff offer a

friendly support. I have no complaint about their in-store logistics services”. However,

DN3_M18 complained about prices being wrongly stated on products sometimes and “due to

its small size, supermarkets could not offer a wide variety of food choices”. HCM3_F35

showed her satisfaction when her favourite supermarket offers a small and nicely designed

bag, in which consumers can leave their unwanted products, located near a cashier counter

before checking out. She explained “I could not find these bags at other supermarkets,

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normally consumers might randomly put on the way to the cashier”. Furthermore, shopping

carts have been mentioned, thanks to clean and spacious shopping carts with many designed

choices which offer a seat for a baby, HCM3_F35 feel safe and extremely happy to shop at a

supermarket. Another note related to in-store logistics, CT2_F35 commented that discounted

products should be checked constantly and neatly arranged, when consumers choose these

products, it always makes it a bit messy there. She also noted “A supermarket should not put

these discounted products near a main entrance gate, I feel not very nice and neat”.

With P2_Q25, when asked about a loyalty level regarding to supermarket brand name,

35% of the respondents gave 3 points if considering on scale 1 to 5. There are 10% of the

respondents showing that they have no loyalty at all. The 55% of the participants showed

their loyalty commitments to supermarkets due to many reasons provided, such as,

convenient location advantages, habit, trust, having loyalty cards, high level of satisfaction,

good store image and brand image perceived.

With P2_Q26, when asked about the satisfaction level of services offered, a majority of

the respondents showed their satisfaction and started to explain why they are satisfied. Most

of them mentioned about how good they feel at getting a respected and supportive behaviour

from supermarket staff. For them, this factor is very important. Other in-store services and

online services had also been mentioned. They all agreed that the more good services offered,

the better consumer returning ratio is.

With P2_Q27, the respondents started to list many factors affecting their choices in

favourite supermarkets chosen for grocery shopping. Diversified goods with good quality

provided, friendly and supportive staffs, reasonable prices and convenient store accessibility,

logical decoration are their top criteria. However, they also explained that they love to shop at

supermarket X because supermarket X offer good quality fresh food with an affordable price

and specific products that other supermarkets do not have, but stores from supermarket X are

always located far away from the city centre, consumers choose to be loyal to supermarket Y

due to other reasons. Some respondents mentioned about the level of trust in supermarket

brand names, good word-of-mouth from other consumers and clean atmosphere also are their

criteria.

With P2_Q28, when asked about whether price is the main factor of choosing which

supermarkets respondents should use, 80% of the participants said “NO”, 20% of them said

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“YES”. It can be easily seen that the group saying “Yes” has a lower income compared to the

other group: they have a tight budget for grocery spending. Therefore, prices are considered

as the most important factor and they accept products with normal quality, they understand

how consumers expect to have a premium quality if they do not want to pay more. Another

group claimed that although price is an important factor because consumers have different

income levels, an affordable price is mentioned above depending on consumers’ income

levels and how to choose supermarkets to go for shopping depends on many factors. “After

considering an acceptable product quality, price and habit might be next criteria” some

respondents said. Respondents from higher income group have clearly stated that “There is

no room for expecting a lower price charged if consumers want a premium product and

excellent other attached services provided, in this case, prices are not a big problem, we are

happy to pay more to get that such premium offers”.

With P2_Q29, when asked how supermarkets’ brand names affect consumer choices, a

majority of respondents agreed that brand names do significantly influence their choices, it

depends on how retail brand names were positioned and the image created. For example, with

long-time good reputation built, supermarkets might create trust in consumer mind that their

products and services offered are guaranteed. In addition, word of mouth from consumers

who do experience a supermarket is also important. On the other hand, some consumers said

that a retail brand name does not affect their choices, such as DN4_F19, HN5_F60,

HCM2_F28. HN5_F60 stated that “A HABIT is more important than a brandname, in my

case, I usually go to supermarket A, in the future, if the supermarket decided to change their

brand name, I would still choose it regardless of the brand name they want to change to

because I am used to where products are located and I love their shopping atmosphere.

However, if they changed their business model and strategies, changed everything, I would

need to reconsider”

With P2_Q30, when asked about whether consumers agree with a following statement:

“I choose supermaket A because of its good store image created”. 50% of the respondents

explained that store image is a crucial factor, in the case that other factors match or exceed

their expectations but they might feel annoyed and unpleasant if bad store image provided

such as cramped and dirty in-store atmosphere, illogically allocated shelves as well as

products, unfriendly, irresponsible and unsupportive in-store staff. They all argued that they

cannot be satisfied with supermarkets in such circumstances and emphasised that to be loyal

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with a specific supermarket brand name, they have considered many factors, and store image

seems to be an important factor. However, the rest explained that store image seems not to

significantly affect their choices, they argued that being a supermarket, at least store image

should be above average in order to make it work and compete with others.

With P2_Q31, as being given the situation as follow “Suppose that there are two

different supermarkets that you feel satisfied, all other factors are the same, one of these is a

domestic brand name, another is foreign brand name, which one will you choose? Why?”,

14% of the respondents said that a foreign brand name and a domestic brand name do not

affect their choices, they have considered many other factors, and moved around

supermarkets if needed. BD3_F26 claimed “each brand name or supermarket have their own

strengths and advantages which offer specific products or services that other supermarkets

do not. Therefore, I am happy to move around them to get the best things”. 28.5% of the

participants chose foreign brand name supermarkets, even if foreign and domestic ones offer

them the same products or services. They feel more trusting with a foreign brand name which

often provides better products and professional services, the name of brand name can classify

customer segmentation. Roughly 57.5 % of the respondents chose a domestic brand name if

other factors offered are similar. They all claimed that being Vietnamese, they are so happy

to support the development of domestic firms, give their contributions to help domestic

supermarkets generate and position their brand names in consumers’ minds. However, I

emphasised that their choices only happen if other factors offered are similar. Besides that,

they showed their excitement if a domestic firm creates a nice foreign brand name, even the

name might be an abbreviation of a group of Vietnamese words, it sounds more interesting to

them.

With P2_Q32, when asked “In your family, who are in charge with buying grocery

products? How many people in your house now? Do you cook/eat separately or together?”,

90% of the respondents said that a housewife is in charge with grocery shopping and daily

food. Normally, in Vietnam, those who stay in the same house which include two to eight

people always share their foods at every single meal, in other words, they do not eat

separately, those who are in charge with cooking will cook for the whole family. 10% of the

participants showed that due to the nature of their jobs, they could be not in charge with

cooking, the husbands usually go to supermarkets or traditional markets for shopping.

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With P2_Q33, when asked “Where do you usually go for daily food and grocery?”, 52%

of the respondents said that they often go to traditional markets to immediately and easily

grab what they want for daily food cooking. However, for other grocery products, they have

two choices, if they need something immediately, they prefer to go to some small private

shops located near their houses to get it; if they want to purchase some products which can be

used in long-term and with a large amount, they will choose supermarkets which offer a

wider choice of products. They also buy food at supermarkets as much as they can. 48% of

the participants always buy their food and grocery products at supermarkets due to many

reasons as follows: being a housewife, they have time to shop at supermarkets every day or

some times per week; due to the nature of work, they have no time to go traditional markets

each morning, supermarkets will be their choice in the evening. Besides that, some

respondents prefer the relaxing feelings of shopping at supermarkets,

With P2_Q34, as being asked “Are you loyal to a supermarket brand name or their

specific store?”, 57% of the respondents admited that they are loyal to a specific store of a

supermarket brandname, surprisingly, 100% of these consumers mentioned about convenient

store accessibility in which it is located near their houses or its convenient locations.

HN2_F30 claimed that she does not have time to move around and be loyal to a specific store

which is located next to her children’s school. Instead of just staying in front of a school to

wait for picking up her son, she pops to the store for shopping around 30 minutes to one hour

every weekday afternoon. 19 % of the participants said that they are loyal to a specific brand

name, they can move around other stores of the same brand name to experience. HCM3_F35

claimed that “When I travel for work, I always give my favourite supermarket brand name a

top priority and find their stores in that place, I love a main colour designed in their stores”.

24 % of the respondents explained that depending on each specific situation, they are happy

to experience other supermarket brand names as well as stores. However, they also emphasise

that they might give a nearest store a go in the case of quick shopping and its convenient

benefits,and go to a store which provides a specialised product. Their choices are flexible and

they might not want to commit themselves to a specific store or brand name.

With P2_Q35, when asked to comment about the following statement that “In Vietnam,

the majority of people who are in charge with buying foods, grocery products is a housewife,

man do not usually deal with this thing”, 80.9% of the respondents said that they agreed with

the above statement. Due to a different culture, in Vietnam, housewives/females are mainly in

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charge with daily cooking for a group of two to eight people who stay in the same house.

They all claimed that the man in their houses might suggest the names of preferred meals but

the final choice significantly depends on the woman, HN1_F 24 said “My dad have no

interest in going to the stalls of vegetable, meat or cooking stuff in supermarkets, he goes

there with us and then go straight to check the counter of electronic products and other

household utensils, he might tell my mum which kinds of food he want to eat but he is not a

final decision maker”, 19.1 % of the participants doubt that the above presented statement

might partly wrong, it depends on each specific family and their situation. Although they

accepted that the statement seems to demonstrate a true thing in Vietnam, but their situations

are different in which their husbands have contributed 50% to 80% of the grocery purchase

decision, 100% of these families are a modern single-family where the wife and husband

equally share jobs and help each other in everything.

In the end of an interview, the interviewer asked interviewees to give their viewpoints

about issues related to customer loyalty. One conclusion can be drawn that consumers who

are from different backgrounds, education levels, income, locations, living styles, gender and

age range have different views about loyalty and which supermarkets they choose to shop as

well as the criteria given (See Appendix 4.1 which briefly presents some direct quotes from

supermarket’s consumer interviews).

4.2.4. Conclusion

The above analysis explored the customer loyalty perception or behaviour of customers

from the Vietnamese supermarket sector and traditional retail channels. TRUST and HABIT

were considered as factors influencing customer loyalty. Therefore, after this interview

process, the literature review on the relationship between customer loyalty and TRUST and

HABIT were investigated and added into the original literature review section, followed

by added hypotheses in section 2.4.13.2 (H25 and H26).

“H25: Trust positively affects customer perceived value

H26: Habit positively affects customer loyalty”

Based on this result, building a scale for both TRUST and HABIT constructs were

conducted and added to the originally proposed questionnaire. It is noted that the above

qualitative analysis can examine consumers’ perception and behaviour, in order to understand

the relationship between researched constructs and which level they affect each other,

quantitative research will be conducted in the next two chapters (Chapter 5 and Chapter 6).

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Phase one-step two examines which possible factors might affect their loyalty; the next

two chapters will demonstrate results from quantitative research. The figure 4.1 below will

sumarise main contents presented in chapter 5 and 6.

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Chapter 5

Chapter 6

Figure 4.1: Contents of Chapter 5 and Chapter 6

Structural equation modelling: the relationship between researched

constructs revealed

Multigroup analysis: strategic groups and other differences between on

income, gender, location, age groups, occupation and education levels

Passed non response bias test

67.31% response rate

Passed confirmatory factor analysis after removing two variables

(RBEX4 and RBEX5)

Exploratory factor analysis: 63 remained variables - “Corporate image” has been eliminated.

- “E-service quality” has been divided into two small constructs

Internal consistency (section 5.4):

removed 5 variables

Descriptive statistics

Data screening

3055->2913

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Chapter 5: Phase Two - Quantitative data analysis

Survey Descriptive Statistics and Exploratory Factor Analysis

5.1. Introduction

In this chapter, data preparation and screening will be presented first. In this section,

normality testing will be presented, followed by response rate, response and non-response

bias. Then, the results from descriptive statistics are demonstrated, followed by results from

exploratory factor analysis.

5.2. Data preparation and data screening

5.2.1. Data preparation

Data was created based on the answers collected from questionnaires. Firstly, creating a

codebook is essential (Appendix 3.5), followed by presenting a structured data file. Then, all

data was input to Microsoft Excel 2010 and modified if necessary during examination.

5.2.2. Data screening

5.2.2.1. Missing data

According to Hair et al. (2010), there are many initial steps to undertake before factor

analysis is attempted. All data collected was initially input to Microsoft Excel 2010, and then

it was checked for any data missed. There were 3055 questionnaires collected from 17 March

2018 to 27 July 2018. After checking the raw input data, there were 57 surveys which have

been removed from the data set due to the huge amount of data missed (case screening). Then

data was checked for unengaged responses: participants who enter the exact same value for

every single survey item (meaning they had similarly answered every Likert-scale item).

There were 85 cases of unengaged responses found. These were also removed from the data

set. There were 2913 remaining questionnaires which were coded and input to the software

named SPSS, version 24. The researcher also used the “replace missing value” tool to input

some minor missing values (8 cases). As a result, there were 2913 questionnaires used for

further investigation.

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5.2.2.2. Identification of outliers

“Outliers, or extreme responses, may unduly influence the outcome of any multivariate

analysis. It is an observation with a unique combination of characteristics identifiable as

distinctly different from the other observations” (Hair et al., 2010:64). Hair et al. (2010)

identify four classes of outliers as follows:

1. From “a procedural error”, including a data entry error or wrong coding created.

2. An observation that “occurs as the result of an extraordinary event”. For instance,

when tracking average daily rainfall, a hurricane occurring once or twice in a month

might affect the whole data set.

3. Extraordinary observations, researchers can use their own judgment in the

retention/deletion decision.

4. Observations that “fall within the ordinary range of values on each of the variables”

In this research, all variables have been checked for outliers. According to Hair et al.

(2010:66), setting the threshold for designation of outliers should be done first. The common

approach is “converting the data values to standard scores, which have a mean of 0 and a

standard deviation of 1”. For sample size is higher than 80, outliers typically are defined as

cases with standard scores up to 4. According to Gaskin and Lim (2017), outliers do not

really exist in Likert-scales because respondents’ answers are from 1 to 5 or 1 to 7 depending

on their viewpoints. Outliers should be checked on continuous variables such as age,

experience and income if respondents point out a specific number based on their case. The

boxplot can be used to detect outliers. However, in this study, outlier detection is not even

possible on continuous variables because the researcher created specific questionnaires based

on age and income ranges which were coded as 1, 2, 3, 4 or 5 in the dataset.

Hair et al. (2010:67) stated “Our belief is that they (outliers) should be retained unless

demonstrable proof indicates that they are truly aberrant and not representative of any

observations in the population”. The final decision on retaining these variables which will be

made at the EFA step.

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5.2.2.3. Normality test - statistics

Normality test refers to “the shape of the data distribution for an individual metric

variable and its correspondence to the normal distribution…if the variation from the normal

distribution is sufficiently large, all resulting statistical tests are invalid” (Hair et al.,

2010:71).

A simple statistical test for normality is based on a rule of thumb of the Skewness and

Kurtosis value which can be computed in SPSS. Skewness value demonstrates the balance of

the distribution while Kurtosis represents the height of the distribution. According to Hair et

al. (2010:73), the statistic value (z) for the skewness value and Kurtosis value are calculated

as follows:

zskewness = skewness/√6/𝑁

zkurtosis = kurtosis/√24/𝑁

where N is the sample size, “if either calculated z value exceeds the specified critical

value, then the distribution is non-normal in terms of that characteristic…the most commonly

used critical values are ±2.58 (.01 significance level) and ±1.96, which corresponds to .05

error level” (Hair et al., 2006:82). In this research, all indicators of latent factors and other

variables such as age, income and education level were tested.

The Kolmogorvo-Smirnov test is also used to check normality distribution. The

hypothesis is presented as follows:

H0: A variable shows normality

H1: A variable does not show normality

Sig-value, which is higher than 0.05, indicates that a variable is normally distributed. For

a large sample size, the above test tends to be significant as the p-value is usually equal to

0.000 if any slightly small difference from a normal distribution occurs. In this case, H0 is

rejected. All measurement variables of this research have been checked and non-normal is

revealed as a result (the significance value is 0.000) (see Appendix 5.1). Hair et al. (2010)

recommended that the research should always use both statistical tests and graphical plots to

examine normality. Due to its large sample size (for reasons stated above), normal probability

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plots (P-P or Q-Q plot) were used to re-check the results. According to Palant (2007), plots

reasonably clustered around a straight line indicate normality distribution. All data is used to

examine Q-Q plot, the results showed that the data set is considered as a normal distribution

(Q-Q plot can be used to test every single variable; however, Appendix 5.2 shows Q-Q test

for each construct, the results for each variable are relatively the same). Therefore, the data

were not transformed. Figure 5.1 presents Q-Q plot for measured item “CPV”.

Figure 5.1: Normal Probability Plot

5.2.3. Response rate and Non-response bias

There were 3500 questionnaires printed and soft copies of questionnaires sent to

supermarket consumers of different strategic groups in different ways from 17 March to 27

July 2018, 2356 original printed questionnaires were returned, 699 hard copies of

questionnaires originating from email were returned back by post. In the case of printed

questionnaires, the response rate was 67.31%. Unfortunately, soft copies of the questionnaire

were sent to respondents via multiple channels, so the response rate was impossible to

identify. In total, 3055 questionnaires were returned.

Non-response bias is defined as “not the number of non-respondents, but the possibility

of bias” (Oppenheim, 1992:106, content hull). Saunders et al. (2007) stated that non-

respondents who refuse to respond to questionnaires or respond late might generate different

findings for specific phenomena. In this research, the non-response bias test was examined

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based on questionnaires returned late (Armstrong and Overton, 1977). The data collected was

divided into four quarters based on the order of receipt of questionnaires. Independent sample

t-test was used to investigate the difference between first quarter and last quarter. A new

qualitative variable was created named “NONBIAS” with the value of 1 in the dataset

represented for the first quarter, the value of 2 represented for the fourth (last) quarter. All

112 measured items were checked. The results of independent samples t-test are shown in

Appendix 5.3. According to Pallant (2007), if the significance level of Levene’s test is less

than 0.05, the t-value examined will be placed at the second line (equal variances not

assumed); if the significance level of Levene’s test is more than 0.05, the t-value examined

will be placed at the first line (equal variances assumed). At t-test column, that Sig (2-tailed)

is lower than 0.05 means a significant difference between two examined groups occurred and

that Sig (2-tailed) is higher than 0.05 mean no significant difference occurred between two

examined groups (in this case early and late respondents).

In this research (see Appendix 5.3), the majority of of p-values (Sig 2 tailed) are higher

than 0.05, 9 out of 112 variables having a p-value lower than 0.05. Therefore, at 95%

confidence interval, there were no statistically significant differences in the mean values for

all examined measurement variables between early and late respondents.

5.3. Descriptive statistics

5.3.1. Respondent demographic data

In data collected via different channels (email, face-to-face and post) there were 143

questionnaires removed from the dataset due to issues of uncompleted information and

unengagement. The demographic information from the remaining 2913 respondents will be

briefly presented in Table 5.1. There are around 500-700 surveys collected at each targeted

city; roughly 69% female respondents and 30.5% male; 30.3 % of respondents are students,

office staff and housewives are 24.5% and 27.9% respectively; monthly income of

respondents is dominantly around GB£170-680; the majority of respondents aged from 18 to

22 (41.5%), 23 to 30 (21.1%), above 55 (17.2%) and 85% of participants possess A levels.

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LOCATION Frequency Percent

Hanoi 727 25

Da Nang 488 16.8

Ho Chi Minh 679 23.3

Binh Duong 517 17.7

Can Tho 502 17.2

Total 2913 100

GENDER Frequency Percent

Male 889 30.5

Female 2002 68.7

Prefer not to say 22 0.8

Total 2913 100

OCCUPATION Frequency Percent

Students 882 30.3

Self-employment 217 7.4

Office staffs 714 24.5

Housewife 813 27.9

Unemployment 19 0.7

Prefer not to say 268 9.2

Total 2913 100

MONTHLY INCOME Frequency Percent

Lower than 5 million VND (170 GBP) 1275 43.8

From 5 to 10 million VND (170-340GBP) 853 29.3

From 10 to 20 million VND (340-680GBP) 686 23.5

From 20 to 50 million VND (680-1700 GBP) 65 2.2

Higher than 50 million (above 1700 GBP) 34 1.2

Total 2913 100

AGE RANGE Frequency Percent

Under 18 25 0.9

18-22 1210 41.5

23-30 616 21.1

31-40 303 10.4

41-55 259 8.9

Above 55 500 17.2

Total 2913 100

EDUCATION LEVEL Frequency Percent

GCSE’s 235 8.1

A levels 2477 85

College, undergraduate 201 6.9

Total 2913 100

Table 5.1: Summary of respondents’ profile

How demographic information affecting the relationship between constructs will be

examined in the secrtion covering multigroup analysis (section 6.6.3.4).

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5.3.2. Shopping behaviour - Respondents’ choices

In this research, shopping behaviour is also briefly investigated through 20 questions.

The results are presented at Appendix 5.5.

5.3.3. Mean and standard deviation values for all constructs

Twenty-one constructs with all variables were examined in this research. The standard

deviation values of all measured items are considered relatively high. As noted, a 5-point

Likert scale has been used to measure all items, with 1 meaning “strongly disagree”, 2

“disagree”, 3 “neutral = neither agree nor disagree”, 4 “agree” and 5 “strongly agree”.

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Descriptive Statistics

Minimum Maximum Mean Std.

Deviation

CPV1 1 5 3.57 0.887

CPV2 1 5 3.74 0.914

CPV3 1 5 3.71 0.870

CPV4 1 5 3.80 0.854

CPV5 1 5 3.69 0.890

CPV6 1 5 3.44 0.909

CS1 1 5 3.08 0.889

CS2 1 5 3.42 0.847

CS3 1 5 3.53 0.844

CS4 1 5 3.45 0.901

CS5 1 5 2.28 1.268

CL1 1 5 3.46 0.950

CL2 1 5 2.88 1.063

CL3 1 5 3.38 0.915

CL4 1 5 3.53 0.949

CL5 1 5 3.39 0.995

ISL1 1 5 3.59 1.021

ISL2 1 5 3.74 0.953

ISL3 1 5 3.94 0.948

ISL4 1 5 3.97 0.935

ISL5 1 5 3.89 0.908

ISL6 1 5 3.76 0.986

ISL7 1 5 3.88 0.929

SQ1 1 5 3.34 0.930

SQ2 1 5 3.45 0.879

SQ3 1 5 3.63 0.848

SQ4 1 5 3.45 0.919

SQ5 1 5 3.69 0.908

SQ6 1 5 3.75 0.909

ESQ1 1 5 3.19 0.993

ESQ2 1 5 3.26 1.021

ESQ3 1 5 3.42 0.952

ESQ4 1 5 3.51 0.950

ESQ5 1 5 3.58 0.937

ESQ6 1 5 3.63 0.952

ESQ7 1 5 3.30 1.002

ESQ8 1 5 3.36 0.937

ESQ9 1 5 3.44 0.938

ESQ10 1 5 3.50 0.954

PROQ1 1 5 3.88 0.910

PROQ2 1 5 3.87 0.855

PROQ3 1 5 3.60 0.868

PROQ4 1 5 3.64 0.871

PRICE1 1 5 3.65 0.906

PRICE2 1 5 3.44 1.037

PRICE3 1 5 3.57 0.899

CUSER1 1 5 3.05 1.076

CUSER2 1 5 3.48 1.060

CUSER3 1 5 3.31 1.014

CUSER4 1 5 3.36 0.970

CUSER5 1 5 3.79 0.986

CUSER6 1 5 3.61 1.042

CUSER7 1 5 3.58 0.980

CUSER8 1 5 3.45 1.044

CUSER9 1 5 3.41 1.008

CUSER10 1 5 3.48 1.008

CUEXP1 1 5 3.59 0.894

CUEXP2 1 5 3.63 0.910

CUEXP3 1 5 3.70 0.871

CUEXP4 1 5 3.70 0.940

RBEX1 1 5 3.48 0.956

RBEX2 1 5 3.59 0.894

RBEX3 1 5 3.37 1.001

RBEX4 1 5 3.59 0.909

RBEX5 1 5 3.58 0.901

RBEX6 1 5 3.06 1.042

STIMA1 1 5 3.54 0.889

STIMA2 1 5 3.47 0.926

STIMA3 1 8 3.55 0.879

STIMA4 1 5 3.67 0.891

STIMA5 1 5 3.56 0.904

STIMA6 1 5 3.59 0.877

STIMA7 1 5 3.71 0.875

COIMA1 1 5 3.74 0.870

COIMA2 1 5 3.81 0.865

COIMA3 1 5 3.65 0.893

CSR1 1 5 3.55 0.879

CSR2 1 5 3.48 0.898

CSR3 1 5 3.63 0.863

CSR4 1 5 3.65 0.864

CSR5 1 5 3.70 0.852

CSR6 1 5 3.71 0.893

TRUST1 1 5 3.61 0.902

TRUST2 1 5 3.71 0.851

TRUST3 1 5 3.69 0.877

TRUST4 1 5 3.62 0.907

HABIT1 1 5 3.71 0.953

HABIT2 1 5 3.65 0.937

HABIT3 1 5 3.67 0.925

STAC1 1 5 3.75 0.967

STAC2 1 5 3.82 0.940

STAC3 1 5 3.84 0.940

ALA1 1 5 3.14 1.021

ALA2 1 5 3.38 0.965

ALA3 1 5 3.19 1.026

ALA4 1 5 3.29 1.006

SWC1 1 5 3.04 1.063

SWC2 1 5 2.95 1.102

SWC3 1 5 3.17 1.040

SWC4 1 5 3.24 1.062

SWC5 1 5 3.21 1.078

SWC6 1 5 3.33 1.054

LPRO1 1 5 3.59 0.982

LPRO2 1 5 3.73 0.938

LPRO3 1 5 3.72 0.941

LPRO4 1 5 3.65 0.941

LPRO5 1 5 3.53 0.986

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LPRO6 1 5 3.44 1.061

PROE1 1 5 3.65 0.874

PROE2 1 5 3.79 0.896

PROE3 1 5 3.81 0.894

Table 5.2: The descriptive statistics for all items in the dataset

That the mean values of 4 variables of CL (customer loyalty) are from 3.38 to 3.53,

except that of CL2 (“I am willing to pay more as compared to other retailers for the products

I buy from this retailer”) which is 2.88 shows that participants might be loyal to supermarkets

but it does not mean that they will be happy to pay more for that loyalty.

That RBEX6 represents for “Stories of this brand stimulate my curiosity” having a mean

of 3.06 indicates that respondents seem to be neutral to this statement.

That SWC1 (Switching to other providers will bring economic loss) and SWC2

(Switching to other providers will bring psychological burden) having mean values of 3.04

and 2.95 respectively also shows that participants chose to be neutral on these statements.

Maybe, they could not find a huge switching cost loss when moving to shop at other retailers.

That respondents chose average of 3.19 and 3.26 for ESQ1 and ESQ2 (“Organisation

compensates me when what I ordered does not arrive on time”, “Organisation picks up items

I want to return with minimum hassle” respectively) means that they do not really agree or

disagree about these statements, since return services in Vietnam are still not developed.

ALA1 represents for “Probably, I would be satisfied with another company”, has a mean

value of 3.14, and people tend to agree with this statement but not totally.

ISL5 stating “In this supermarket, all products can be easily reached” and CPV4

“Compared to the price we pay, we get reasonable quality”, showmean values of 3.8 and 3.89

respectively, meaning that a majority of respondents agree with these statements.

5.4. Internal consistency

All 112 measured items were examined for reliability (internal consistency) by checking

Cronbach’s alpha coefficients and correlation between variables (including inter-item

correlation and item-total correlations). Hair et al. (2010) and Pallant (2007), stated that the

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coefficients of inter-item correlation should be more than 0.3 and that of item-total

correlation should be higher than 0.5; if not, the variables should be removed from the

dataset. A Cronbach’s alpha coefficient of constructs should be over 0.6 and higher than

Cronbach’s alpha if item deleted. The results of internal consistency between measured items

in same constructs are statistically presented at Appendix 5.6. The majority of variables in the

same construct satisfy the above internal consistency criteria apart from the 5 different

variables which are CPV6, CS5, RBEX6, STIMA6, TRUST4. The reasons for dropping

these five variables before conducting exploratory factor analysis are: as presented at

Appendix 5.6, customer perceived value has 6 variables: CPV1 to CPV6. The coefficients of

all inter-item correlation are from 0.302 to 0.599 (higher than 0.3) and all coefficients are

significant at 1 %. All coefficients of item-total correlation are higher than 0.5 except CPV6

(0.497). The Cronbach’s alpha value of customer perceived value without CPV6 is 0.825;

therefore the researcher decided to drop CPV6 from the dataset. Similarly, as presented in

Appendix 5.6, customer satisfaction has 5 variables: CS1 to CS5. The coefficients of the

majority of inter-item correlation are from 0.447 to 0.649 and these values are significant at 1

%, except CS5 which is not significant at 1% and presents alow correlation with other

variables in the same construct. Cronbach’s alpha coefficient of CS if CS5 is deleted is 0.827

compared to the current low value of 0.659. Therefore, CS5 has been removed from the

dataset. As presented in Appendix 5.6, retail brand experience has 6 variables: RBEX1 to

RBEX6. The coefficients of all inter-item correlation are from 0.318 to 0.594 and all

variables are significant at 1 %. All coefficients of item-total correlation are higher than 0.5

except RBEX6, the Cronbach’s alpha coefficient of retail brand experience is 0.834 and if

RBEX6 was removed, the Cronbach’s alpha value increases to 0.844. Therefore, RBEX6

was removed from the dataset. As presented in Appendix 5.6, store image has 7 variables:

STIMA1 to STIMA7. The coefficients of all inter-item correlation are from 0.304 to 0.614

and its values are significant at 1 %. All coefficients of item-total correlation are higher than

0.5 except STIMA6, the Cronbach’s alpha coefficient of store image is 0.848 and if STIMA6

is removed, the Cronbach’s alpha value increases to 0.860 and other factors are satisfied.

Therefore, STIMA6 was eliminated from the dataset.

As presented in Appendix 5.6, trust has 4 variables: TRUST1 to TRUST4. The

coefficients of all inter-item correlation are from 0.527 to 0.758 and its values are significant

at 1 %. All coefficients of item-total correlation are satisfied with the criteria which is higher

than 0.5, the Cronbach’s alpha coefficient of trust is 0.866, if TRUST4 is removed, the value

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of Cronbach’s alpha increases to 0.876. Therefore, the researcher decided to drop

TRUST4 from the dataset and other factors are satisfied.

In conclusion, there are 111 measured variables used in the questionnaire; based on the

above analysis, 5 items were eliminated from the dataset before further analysis, including:

CPV6, CS5, RBEX6, STIMA6, TRUST4.

5.5. Exploratory factor analysis

5.5.1. The results from Exploratory factor analysis

All variables after internal consistency checking were used for the next step (EFA). Due

to a huge number of variables, EFA was iterated and computed many times until a clean

pattern matrix was revealed. In this analysis step, Principal axis factoring and Promax

rotation method were used because of its nature and these methods could generate a pattern

matrix that facilitates later confirmatory factor analysis. There were 49 variables eliminated.

The results of Barlett test of sphericity is significant with chi-square is 105721.538 and df is

1953, p-value is 0.000< 0.0001. The KMO value is 0.966 which is higher than 0.5 (Appendix

5.7.) It means that the data set was appropriate for factor analysis and the following results

are statistically significant (Hair et al., 2010). Appendix 5.8 shows 21 factors extracted with

63 remained variables, with 63.50% of total variance. The results show that the eigenvalues

of all factors are higher than 1, the current variables and data are reliable; all factor loading

coefficients are higher than 0.5 and no cross-loading factors found in pattern matrix.

Therefore, there is no problem with convergent and discriminant validity. Other variables

were dropped one by one from the data set because of its low factor loadings and cross-

loading problems and the Cronbach’s alpha of all extracted constructs shows its values of

higher than 0.7. The name of each remaining construct was coded at the dataset as the below

table (Table 5.3).

204

Variables Deleted variables Remained Variables Cronbach's alpha Before After

CPV

CPV1 CPV1

0.79 6 3

CPV2 CPV2

CPV3 CPV3

CPV4 CPV4

CPV5 CPV5

(Customer perceived value) CPV6 CPV6

CS

CS1 CS1

0.819 6 3

CS2 CS2

CS3 CS3

CS4 CS4

CS5 CS5

(Customer satisfaction) CS6 CS6

CL

CL1 CL1

0.8 5 3

CL2 CL2

CL3 CL3

CL4 CL4

(Customer loyalty) CL5 CL5

ISL

ISL1 ISL1

0.769 7 3

ISL2 ISL2

ISL3 ISL3

ISL4 ISL4

ISL5 ISL5

ISL6 ISL6

(In-store logistics) ISL7 ISL7

SQ

SQ1 SQ1

0.813 6 3

SQ2 SQ2

SQ3 SQ3

SQ4 SQ4

SQ5 SQ5

(Service quality related to service employees) SQ6 SQ6

ESQX2

ESQ1 ESQ1

0.796

10 6

ESQ2 ESQ2

ESQ3 ESQ3

ESQ4 ESQ4

ESQ5 ESQ5

(E-service quality related to E-S-QUAL) ESQ6 ESQ6

ESQX1

ESQ7 ESQ7

0.86 ESQ8 ESQ8

ESQ9 ESQ9

(E-service quality related to W-S-QUAL) ESQ10 ESQ10 (2 FACTORS)

PROQ

PROQ1 PROQ1

0.799 4 3 PROQ2 PROQ2

PROQ3 PROQ3

(Product quality) PROQ4 PROQ4

PRICE PRICE1 PRICE1

0.807 3 3 PRICE2 PRICE2

(Price) PRICE3 PRICE3

CUSER

CUSER1 CUSER1

0.797 10 2

CUSER2 CUSER2

CUSER3 CUSER3

CUSER4 CUSER4

CUSER5 CUSER5

CUSER6 CUSER6

CUSER7 CUSER7

CUSER8 CUSER8

CUSER9 CUSER9

(Customer service) CUSER10 CUSER10

CUEXP

CUEXP1 CUEXP1

0.848 4 3 CUEXP2 CUEXP2

CUEXP3 CUEXP3

(Customer experience) CUEXP4 CUEXP4

205

RBEX

RBEX1 RBEX1

0.817 6 4

RBEX2 RBEX2

RBEX3 RBEX3

RBEX4 RBEX4

RBEX5 RBEX5

(Retail brand experience) RBEX6 RBEX6

STIMA

STIMA1 STIMA1

0.805 10 3

STIMA2 STIMA2

STIMA3 STIMA3

STIMA4 STMA4

STIMA5 STMA5

STIMA6 STMA6

(Store image) STIMA7 STMA7

COIMA (CONSTRUCT DELETED)

COIMA1 COIMA1

3 0 COIMA2 COIMA2

COIMA3 COIMA3

CSR

CSR1 CSR1

0.832 6 3

CSR2 CSR2

CSR3 CSR3

CSR4 CSR4

CSR5 CSR5

(Corporate social responsibility) CSR6 CSR6

TRUST

TRUST1 TRUST1

0.876 4 3 TRUST2 TRUST2

TRUST3 TRUST3

(Trust) TRUST4 TRUST4

HABIT HABIT1 HABIT1

0.82 3 3 HABIT2 HABIT2

(Habit) HABIT3 HABIT3

STAC STAC1 STAC1

0.911 3 3 STAC2 STAC2

(Store accessibility) STAC3 STAC3

ALA

ALA1 ALA1

0.838 4 3 ALA2 ALA2

ALA3 ALA3

(Alternative attractiveness) ALA4 ALA4

SWC

SWC1 SWC1

0.813 6 3

SWC2 SWC2

SWC3 SWC3

SWC4 SWC4

SWC5 SWC5

(Switching costs) SWC6 SWC6

LPRO

LPRO1 LPRO1

0.859 6 3

LPRO2 LPRO2

LPRO3 LPRO3

LPRO4 LPRO4

LPRO5 LPRO5

(Loyalty programs) LPRO6 LPRO6

PROE PROE1 PROE1

0.847 3 3 PROE2 PROE2

(Promotion effect) PROE3 PROE3

Total 111 63

Table 5.3: All remained variables after EFA

Source: Results from the author’s data analysis

206

5.5.2. Conclusion

There were 21 factors extracted with 63 remained variables which are named above, all

constructs achieved reliability as all Cronbach’s alpha coefficients are higher 0.7, there is no

problem with convergent and discriminant issues in exploratory factor analysis (loading

coefficients are higher than 0.5 and no cross-loading existed). Appendix 5.10 presents names

of all measurement variables remaining after EFA. All variables of COIMA (“corporate

image” construct) have been eliminated from the dataset due to convergent and discriminant

issues. “E-service quality” construct has been divided into two small constructs,

including e-service quality related to a core e-service quality scale (E-S-QUAL of ESQ4,

ESQ5 and ESQ6), and e-service quality related to website quality scale (W-S-QUAL of

ESQ7, ESQ8 and ESQ9). It can be noted that manifest variables for “e-service quality”

constructs used in this research were created and tested by Zemblyte (2015). Via EFA

process and with interaction between a number of factors, the statistical results revealed that

scales for “e-service quality” constructs should be divided into two different constructs. Then,

the researcher named these as noted above. In conclusion, two constructs for e-service

quality will be presented in the revised model and there is no “corporate image” factor

included. It means that hypothesis 23 and hypotheis 24 will not be able to be investigated,

and hypotheses related to e-service quality (H17X1 and H17X2) will be changed to H17A,

H17B, H17C and H17D which are:

H17A: E-service quality about X1 (W-S-QUAL) has a significant positive effect on customer

perceived value

H17B: E-service quality X2 (E-S-QUAL) has a significant positive effect on customer

perceived value

H17C: E-service quality X1 (W-S-QUAL) has a significant positive effect on customer

loyalty

H17D: E-service quality X2 (E-S-QUAL) has a significant positive effect on customer

loyalty

The next part will demonstrate the revised model after EFA and the next chapter will

present construct validation and hypothesis testing.

5.6. The revised model

207

+ H6

+H14

+H12A

+H7B +H16 +H25

+H26 +H18 +H15

+H11B

-H10B

+H11A

+H9B

H6

+ H7A

+H8

+H

22

B

Figure 5.2: The revised model for main study

`

In-store

logistics

ssss

A core e-

service

quality

Service

quality

Customer

service

Customer

experience

Retail brand

experience

Product

quality

Price Corporate social

responsibility

Store

image

Habit

Trust

Switching

costs

Alternative

attractivenes

s

Loyalty

programs

ss

Promotion

effects

CUSTOMER

PERCEIVED VALUE

Store

accessibility

CUSTOMER

LOYALTY

Gender Age Location

s

Income Strategic groups

CUSTOMER

SATISFACTION

Control variables

3 items 3 items 3 items 3 items 3 items 3 items 3 items 3 items

3 items 2 items

3 items

4 items

3 items

3

ite

ms

3 items

3 items

Website

quality

scale

3 items

3 items

208

Chapter 6: Confirmatory factor analysis and structural equation modelling

(Construct validation and hypothesis testing)

6.1. Introduction

This chapter is going to examine construct reliability and validity and test hypotheses

proposed in section 2.5.13.2, including factors directly influencing customer perceived value,

customer satisfaction, customer loyalty, and multigroup analysis across groups.

6.2. Unidimensionality - Initial model fit

According to Hair et al. (2010:696), “Unidimensionality measures mean that a set of

measured variables (indicators) can be explained by only one underlying construct”. In order

to investigate construct unidimensionality, initial model fit and other factors such as factor

loadings (acceptable above 0.5), modification index and standardised residual should be

checked.

209

Figure 6.1: Results from CFA_1strun

210

All factors extracted, including 63 variables were input to AMOS version 24 for

confirmation factor analysis. The initial goodness of fit was checked and presented as

follows:

Measure Estimate Threshold Interpretation

CMIN 6201.062 -- --

DF 1680 -- --

CMIN/DF 3.691 <5 Acceptable

CFI 0.956 >0.95 Excellent

SRMR 0.029 <0.08 Excellent

RMSEA 0.03 <0.06 Excellent

PClose 1 >0.05 Excellent

Table 6.1: Model fit of CFA_1strun

(Source: Data analysis results from the author)

CFA_1strun: P-value =0.000, cmin/df = 3.691 < 5 which is the threshold of acceptable

model, CFI=0.956>0.95, SRMR=0.029<0.08, RMSEA=0.030<0.06 and

PCLOSE=1.000>0.05, TLI=0.949 >0.9, GFI=0.928>0.9. It means that the model fit is

confirmed as excellent (Kelloway, 1998; Hair et al., 2010; MacCallum et al., 2009;

Tabachnick and Fidell, 2007).

There are some ways to improve model fit by using MI (modification index) and residual

moments to reduce CMIN/DF which expected to be lower than 3 to get the excellent level of

fit. The threshold for MI was set above 4 and covariance had been drawn between the

following variables within its constructs: e56-e58 (PROQ2-PROQ3), e45-e46 (TRUST1-

TRUST3), e25-e26 (PROE2-PROE3), e2-e3(ESQ7-ESQ9), e32-e33(HABIT1-HABIT3),

e35-e36(PRICE1-PRICE3), e62-e63(STIMA1-STIMA3), e47-e48(CS1-CS2), e41-e42

(CUEXP2-CUEXP3), e51-e52(CSR3-CSR5), e11-e12(CPV2-CPV4), e57-e58(PROQ1-

PROQ3), e17-e18(ISL1-ISL3), e28-e29(SQ5-SQ6), e39-e40(RBEX1-RBEX5), e8-

e9(LPRO2-LPRO4), e23-e24(CL3-CL5), e14-e15(SWC2-SWC4), e38-e40 (RBEX4-

RBEX5). According to Hair et al. (2010), using MI is acceptable to improve model fit, but

covariance should be drawn between variables in the same construct.

After MI, the whole model was run again, named CFA_2nd

run. The result is presented as

follows: CFA_2nd

run: P-value =0.000, cmin/df = 3.294 < 5 which is the threshold of

acceptable model, CFI=0.963>0.95, SRMR=0.024<0.08, RMSEA=0.028<0.06 and

PCLOSE=1.000>0.05, TLI=0.956 >0.9, GFI=0.936>0.9. The model is considered as an

excellent fit (Appendix 6.1).

211

6.3. Construct validity

“Construct validity is the extend to which a set of measured items actually reflects the

theoretical latent construct those items are designed to measure” (Hair et al., 2010:708). The

following contents will provide the criteria for construct validity test, followed by statistical

results from construct validity testing.

6.3.1. Convergent and discriminant validity

6.3.1.1. Convergent validity

That all indicators of a specific construct converge or share a high proportion of variance

is known as convergent validity (Hair et al., 2010). There are many ways to examine

convergent validity through factor loading, construct reliability and average variance

extracted. Firstly, factor loadings which should be higher than 0.5 or ideally 0.7 or higher.

Secondly, the average variance extracted (AVE) is the mean variance extracted for the items

loading on a construct. It is calculated by using standardised loading:

AVE= ∑ 𝑳𝒊^𝟐𝒏

𝒊=𝟏

𝒏

While Li represents the standardised factor loading and i is the number of items. That the

value of AVE is 0.5 or higher suggests adequate convergence.

Thirdly, construct reliability (composite reliability) is also considered an indicator of

convergent validity, it can be computed from the squared sum of factor loadings (Li) for each

construct and the sum of the error variance terms for a construct (ei) as follows:

CR= (∑ 𝑳𝒊)^𝟐𝒏

𝒊=𝟏

(∑ 𝑳𝒊)^𝟐𝒏𝒊=𝟏 + (∑ 𝒆𝒊)𝒏

𝒊=𝟏

The value of construct reliability is higher than 0.7 suggesting a good reliability.

6.3.1.2. Discriminant validity

“Discriminant validity is the extent to which a construct is truly distinct from other

constructs” (Hair et al., 2010:710). There are two criteria used for discriminant validity: the

variance extracted value should be higher than maximum shared variance (MSV) which is the

212

square of inter-correlation between two constructs and the square root of AVE should be

greater than inter-construct correlations (Fornell and Larcker, 1981).

6.3.1.3. Criteria summarizing

The criteria can be summarised as follows:

Convergent validity: CR > 0.7, AVE ≥ 0.5

Discriminant validity: AVE>MSV and the square root of AVE should be greater than inter-

construct correlations.

6.3.2. Results from construct validity

6.3.2.1. Convergent validity

Three main criteria of convergent validity were examined by the researcher. The results

are shown as follows:

213

Loadings Squared

loadings AVE 1-squared loading CR

ESQX1

ESQ8 <--- ESQX1 0.844 0.712

0.707

0.288 (Total loadings)^2 6.360

ESQ7 <--- ESQX1 0.862 0.743 0.257 total (1-squared loading) 0.879

ESQ9 <--- ESQX1 0.816 0.666 0.334 CR 0.879

STAC

STAC2 <--- STAC 0.91 0.828

0.665


STAC3 <--- STAC 0.879 0.773 0.227 total (1-squared loading) 1.006

STAC1 <--- STAC 0.627 0.393 0.607 CR 0.853

LPRO

LPRO3 <--- LRPO 0.853 0.728

0.672


LPRO2 <--- LRPO 0.818 0.669 0.331 total (1-squared loading) 0.985

LPRO4 <--- LRPO 0.786 0.618 0.382 CR 0.860

CPV

CPV3 <--- CPV 0.742 0.551

0.580


CPV2 <--- CPV 0.795 0.632 0.368 total (1-squared loading) 1.261

CPV4 <--- CPV 0.746 0.557 0.443 CR 0.805

SWC

SWC3 <--- SWC 0.766 0.587

0.626


SWC4 <--- SWC 0.791 0.626 0.374 total (1-squared loading) 1.123

SWC2 <--- SWC 0.815 0.664 0.336 CR 0.834

ALA

ALA4 <--- ALA 0.84 0.706

0.637


ALA3 <--- ALA 0.823 0.677 0.323 total (1-squared loading) 1.090

ALA2 <--- ALA 0.726 0.527 0.473 CR 0.840

ISL

ISL2 <--- ISL 0.7 0.490

0.514


ISL1 <--- ISL 0.771 0.594 0.406 total (1-squared loading) 1.459

ISL3 <--- ISL 0.676 0.457 0.543 CR 0.760

CL

CL4 <--- CL 0.807 0.651

0.571


CL5 <--- CL 0.758 0.575 0.425 total (1-squared loading) 1.288

CL3 <--- CL 0.697 0.486 0.514 CR 0.799

PROE

PROE2 <--- PROE 0.781 0.610

0.602


PROE3 <--- PROE 0.733 0.537 0.463 total (1-squared loading) 1.195

PROE1 <--- PROE 0.811 0.658 0.342 CR 0.819

SQ

SQ5 <--- SQ 0.758 0.575

0.557


SQ6 <--- SQ 0.763 0.582 0.418 total (1-squared loading) 1.328

SQ4 <--- SQ 0.718 0.516 0.484 CR 0.791

HABIT

HABIT2 <--- HABIT 0.768 0.590

0.639


HABIT3 <--- HABIT 0.825 0.681 0.319 total (1-squared loading) 1.083

HABIT1 <--- HABIT 0.804 0.646 0.354 CR 0.841

PRICE

PRICE2 <--- PRICE 0.676 0.457

0.648


PRICE1 <--- PRICE 0.847 0.717 0.283 total (1-squared loading) 1.055

PRICE3 <--- PRICE 0.878 0.771 0.229 CR 0.845

CUEXP

CUEXP2 <--- CUEXP 0.775 0.601

0.635


CUEXP3 <--- CUEXP 0.793 0.629 0.371 total (1-squared loading) 1.096

CUEXP1 <--- CUEXP 0.821 0.674 0.326 CR 0.839

214

TRUST

TRUST2 <--- TRUST 0.863 0.745

0.693


TRUST1 <--- TRUST 0.867 0.752 0.248 total (1-squared loading) 0.920

TRUST3 <--- TRUST 0.764 0.584 0.416 CR 0.871

RBEX

RBEX2 <--- RBEX 0.75 0.563

0.518


RBEX4 <--- RBEX 0.699 0.489 0.511 total (1-squared loading) 1.927

RBEX1 <--- RBEX 0.731 0.534 0.466 CR 0.811

RBEX5 <--- RBEX 0.698 0.487 0.513

CS

CS2 <--- CS 0.805 0.648

0.588


CS1 <--- CS 0.687 0.472 0.528 total (1-squared loading) 1.237

CS3 <--- CS 0.802 0.643 0.357 CR 0.810

CSR

CSR4 <--- CSR 0.804 0.646

0.634


CSR3 <--- CSR 0.806 0.650 0.350 total (1-squared loading) 1.099

CSR5 <--- CSR 0.778 0.605 0.395 CR 0.838

ESQX2

ESQ5 <--- ESQ 0.786 0.618

0.567


ESQ4 <--- ESQ 0.715 0.511 0.489 total (1-squared loading) 1.299

ESQ6 <--- ESQ 0.756 0.572 0.428 CR 0.797

PROQ

PROQ2 <--- PROQ 0.833 0.694

0.623


PROQ1 <--- PROQ 0.781 0.610 0.390 total (1-squared loading) 1.132

PROQ3 <--- PROQ 0.751 0.564 0.436 CR 0.832

CUSER

CUSER1 <--- CUSER 0.761 0.579

0.670


CUSER3 <--- CUSER 0.872 0.760 0.240 total (1-squared loading) 0.660

CR 0.801

STIMA

STIMA2 <--- STIMA 0.733 0.537

0.608


STIMA1 <--- STIMA 0.844 0.712 0.288 total (1-squared loading) 1.177

STIMA3 <--- STIMA 0.757 0.573 0.427 CR 0.822

Table 6.2: Values of CR and AVE of all constructs


All the above results were calculated in the case of the whole model achieving an excellent fit

(CFA_2nd

run) with P-value =0.000, cmin/df = 3.294 < 5 which is the threshold of acceptable

model, CFI=0.963>0.95, SRMR=0.024<0.08, RMSEA=0.028<0.06 and

PCLOSE=1.000>0.05, TLI=0.956 >0.9, GFI=0.936>0.9. The model is considered as an

excellent fit (Figure 6.2). It means that the results from construct validity and discriminant

validity checking are reliable.

215

How to manually calculate the values of CR and AVE for ESQX1 will be presented in

detail below:

(Total loadings)^2 of ESQX1= (0.844+0.862+0.816) ^ 2

The sum of the error variance of ESQX1= total (1-squared loading) = (0.288+0.257+0.334)

Construct reliability of ESQX1 is calculated as follows:

CR (ESQX1) = (Total loadings)^2 of ESQX1

(𝑇𝑜𝑡𝑎𝑙 𝑙𝑜𝑎𝑑𝑖𝑛𝑔𝑠)2𝑜𝑓 𝐸𝑆𝑄𝑋1+𝑡𝑜𝑡𝑎𝑙 (1−𝑠𝑞𝑢𝑎𝑟𝑒𝑑 𝑙𝑜𝑎𝑑𝑖𝑛𝑔)

= (0.844+0.862+0.816)^2

((0.844+0.862+0.816)2+(0.288+0.257+0.334))

= 0.879

Average variance extracted of ESQX1 is calculated as follows:

Total squared loadings of ESQX1= (0.712+0.743+0.666)

AVE (ESQX1) = 𝑡𝑜𝑡𝑎𝑙 𝑠𝑞𝑢𝑎𝑟𝑒𝑑 𝑙𝑜𝑎𝑑𝑖𝑛𝑔𝑠

𝑡ℎ𝑒 𝑛𝑢𝑚𝑏𝑒𝑟 𝑜𝑓 𝑖𝑡𝑒𝑚𝑠 𝑖𝑛 𝑡ℎ𝑒 𝑐𝑜𝑛𝑠𝑡𝑟𝑢𝑐𝑡

= (0.712+0.743+0.666)

3

= 0.707

The CR of ESQX1 is 0.879 which is higher than 0.7, and the value of AVE is 0.707

which is higher than 0.5 and all of loadings of ESQ8, ESQ7, ESQ9 are 0.844, 0.862, 0.816

respectively which are above 0.5. All values including CR, AVE and loading coefficients are

satisfied. Therefore, ESQX1 has no problem with convergent validity.

Applying the same calculation techniques as presented above to investigate a convergent

validity of other factors, all examined constructs have no problem with convergent validity

when composite reliability are all higher than 0.7, the value of AVE of all constructs is higher

than 0.5 and the loading coefficients of all variables in the same constructs are above 0.5 (See

Table 6.2).

In conclusion, the whole model achieved excellent fit and all 21 extracted factors

achieved convergent validity when all CR value of constructs are higher than 0.7, the value of

216

AVE of all constructs are higher than 0.5 and the loading coefficients of all items in each

construct are higher than 0.5. All constructs have no problem with convergent validity.

6.3.2.2. Discriminant validity

By using Amos version 24 to compute the value of maximum shared variance (MSV),

the square root of AVE, inter-construct correlations, the results are shown as follows:

Table 6.3: Results from CFA_2th

run_Discriminant validity checking


Master validity plugin used is from Gaskin and Lim (2016)

As summarised in section 6.3.1.3, the criteria of constructs getting discriminant validity

are: AVE>MSV and the square root of AVE should be greater than inter-construct

correlations. The results from table 6.3 show that all constructs achieved its discriminant

validity except a RBEX construct when the square root of the AVE for RBEX is less than its

correlation with CUEXP and CSR. While the square root of the AVE for RBEX is 0.720, its

correlation with CUEXP and CSR are 0.791*** and 0.727*** respectively, and in this case,

the value of AVE (0.518) is less than the value of MSV (0.626). Therefore, only RBEX could

not get discriminant validity at the second run of CFA (CFA_2nd

run). In order to solve this

problem, RBEX is examined. As the result of CFA_2nd

run, RBEX was found to have strong

correlation with CUEXP, the correlation value is 0.791 and RBEX5 showed its lowest

loading for RBEX with the coefficient of 0.698 (table 6.2). Therefore, RBEX5 was removed

from the model after CFA_2nd

run. CFA_3rd

run was conducted in order to check RBEX

discriminant validity.

217

Table 6.4: Results from CFA_2nd

run, the correlation between RBEX and other

constructs


After removing RBEX5, CFA_3rd

run with P-value =0.000, cmin/df = 3.298 < 5 which is

the threshold of acceptable model, CFI=0.964>0.95, SRMR=0.024<0.08,

RMSEA=0.028<0.06 and PCLOSE=1.000>0.05, TLI=0.957 >0.9, GFI=0.937>0.9. The

model is remaining as excellent fit.


CMIN 5282.769 -- --

DF 1602 -- --





PClose 1 >0.05 Excellent

Table 6.5: Model fit from CFA_3rd

run



run_ Discriminant validity checking


Master validity plugin used is from Gaskin and Lim (2016)

218

The results from table 6.6 show that all constructs achieved their discriminant validity

except a RBEX construct when the square root of the AVE for RBEX is still less than its

correlation with CUEXP. While the square root of the AVE for RBEX is 0.732, its

correlation with CUEXP and 0.788***, and this case, the value of AVE (0.535) is less than

the value of MSV (0.605). Therefore, only RBEX could not get discriminant validity at the

second run of CFA (CFA_3rd

run). In order to solve this problem, RBEX is examined. As the

result of CFA_3rd

run, RBEX was found to have strong correlation with CUEXP, the

correlation value is 0.778 and RBEX4 showed its lowest loading for RBEX with the

coefficient of 0.697. Therefore, RBEX4 was removed from the model after CFA_3rd

run.

CFA_4th

run was conducted in order to check RBEX discriminant validity, other constructs in

the model have no problem with discriminant validity.

Table 6.7: Results from data analysis (CFA_3rd

run)


After removing RBEX4, CFA_4th

run with P-value =0.000, cmin/df = 3.166 < 5 which is





CMIN 4882.727 -- --

DF 1542 -- --





Pclose 1 >0.05 Excellent

Table 6.8: Model fit of CFA_4th

run

219


run_ Discriminant validity checking


At the fourth CFA running (CFA_4th

run), the results showed no discriminant validity

concerns for all constructs when the AVE values were higher than 0.5 and higher than MSV,

the square root value of AVE for all constructs is greater than that of inter-construct

correlations. Therefore, all constructs achieved its discriminant validity. All values of AVE

and CR of 21 constructs were re-calculated (Table 6.10).

Number Constructs CR AVE

1 ESQX1 0.879 0.707

2 STAC 0.853 0.665

3 LPRO 0.86 0.672

4 CPV 0.805 0.58

5 SWC 0.833 0.625

6 ISL 0.76 0.514

7 ALA 0.84 0.636

8 CL 0.799 0.571

9 PROE 0.819 0.601

10 SQ 0.791 0.558

11 HABIT 0.841 0.639

12 PRICE 0.845 0.648

13 RBEX 0.745 0.594

14 CUEXP 0.838 0.634

15 TRUST 0.871 0.693

16 CS 0.809 0.587

17 CSR 0.838 0.634

18 ESQX2 0.797 0.567

19 PROQ 0.832 0.622

20 CUSER 0.801 0.669

21 STIMA 0.822 0.607

Table 6.10: Final results from CFA_4thrun_Values of AVE and CR of all constructs


220

6.3.2.3. Conclusion

There are no convergent validity and discriminant validity concerns for all constructs.

After CFA_4th

run, RBEX5, RBEX4 have been eliminated, there are 61 measured variables

remaining in 21 factors in the dataset. The model is remaining as an excellent fit (Appendix

6.2). The following table summarises the four CFA running:

Measure CMIN/DF CFI SRMR RMSEA Pclose GFI TLI p-value Model fit

CFA_1strun 3.691 0.956 0.029 0.03 1 0.928 0.949 0 With 63 variable, then MI checking Excellent

Estimate

CFA_2ndrun 3.294 0.963 0.024 0.028 1 0.936 0.956 0 Run after MI checking Excellent

CFA_3rdrun 3.298 0.964 0.024 0.028 1 0.937 0.957 0 RBEX5 removed =>62 variables remained Excellent

CFA_4thrun 3.166 0.966 0.024 0.027 1 0.941 0.96 0 RBEX4 removed=>61 variables remained Excellent

Threshold <5 >0.95 <0.08 <0.06 >0.05 >0.9 >0.9 <0.001

Table 6.11: Summarising results of CFA model fit

6.4. Common method bias

X2 DF Delta p-

value

Unconstrained Model 4857.06 1543 X2=0.000

1.000

Zero Constrained Model 4857.06 1543 DF=0

Table 6.12: Results from zero constraints test

(Tool used from Gaskin and Lim, 2017)

It can be noted that P-value is 1.000 >0.05. The null hypothesis cannot be rejected (i.e.,

the constrained and unconstrained models are the same or “invariant”). It was unable to

detect any specific response bias affecting the model. Therefore, no bias distribution test was

made (of equal constraints). With CLF, the model fit remained unchanged. The above result

demonstrated that common method bias is not a threat in this research (Appendix 6.3 presents

full results of common method bias testing).

6.5. Final measurement model fit

As presented above, the model fit after CFA_4th

run is considered as an excellent fit. The

final model fit is demonstrated as below with P-value =0.000, cmin/df = 3.166 < 5 which is




221

6.6. Structural models

6.6.1. Multivariate assumptions

6.6.1.1. Outliers and influentials

“Outliers are observations with a unique combination of characteristics identifiable as

distinctly different from the other observations” (Hair et al., 2010:64). The assumption of

multivariate statistical analyses requires no multivariate outliers. Some methods to detect

outliers in multivariate analysis, are Mahalanobis’S Distance (MD) or Cook’s D. In this

research, Cook’s D method was used.

There are several different thresholds to detect outliers, if its value (Cook’s distance) is

greater than 1, it is an influential record. Therefore, it should be removed from the dataset

before multivariate analysis is conducted. In the graph, the bigger the number presented; the

bigger influence that observation response has on the regression between the examined

variables.

222

Figure 6.2: Results from outlier testing_Cook’s distance analysis

In this research, Cook’s distance analysis was checked three times between many

dependent variables and independent variables to determine if any (multivariate) influential

outliers existed. No case observed a Cook’s distance greater than 1. The values of Cook’s

distances in all cases were lower than 0.035 (very small). Therefore, there is no problem with

multivariate outliers.

6.6.1.2. Multicollinearity analysis

Multicollinearity occurs when two or more independent variables are highly correlated, it

makes interpretation less reliable. The value of tolerance and MAX-VIF in regression can be

223

used to check this phenomenon (Hair et al., 2010). According to Hair et al. (2010), if the

value of tolerance is higher than 0.1 and MAX-VIF is below 10, there will be no

multicollinearity occurring.

224

Table 6.13: Multicollinearity analysis


The result shows that VIF of all constructs checked are lower than 10 and the values of

tolerance are far higher than 0.1. Therefore, there is no problem with multicollineary in this

research.

6.6.2. Structural model validity

After modifying the model fit and drawing the links which represent relationships

between constructs, in this step, 5 variables: INCOME, LOCATION, AGE, GENDER, Q4

(which strategic groups or supermarkets that respondents often choose to shop?) were input

to the model to investigate the relationships between them and 3 dependent variables (CPV,

CS, CL). The initial SEM was created. At SEM_1strun, the model is fit with P-value =0.000,

cmin/df = 9.307, CFI=0.997>0.95, SRMR=0.005<0.08, RMSEA=0.053<0.06 and

PCLOSE=0.207>0.05, TLI=0.955>0.9, GFI=0.995>0.9. The model fits and results are

reliable (see Appendix 6.4 for the model and full statistical results).

225

6.6.3. Results from hypothesis testing

6.6.3.1. Direct effects

At SEM_1strun, the model is fit with P-value =0.000, cmin/df = 9.307, CFI=0.997>0.95,

SRMR=0.005<0.08, RMSEA=0.053<0.06 and PCLOSE=0.207>0.05, TLI=0.955>0.9,

GFI=0.995>0.9. The model is fit and results are reliable. The result shows that CUEXP,

PROQ, RBEX, CSR, INCOME, GENDER, LOCATION, AGE do not affect customer

perceived value (CPV); GENDER, AGE, Q4, STAC do not affect customer satisfaction (CS),

Q4, LOCATION, AGE, GENDER, CSR, PROQ, CPV do not affect customer loyalty (CL)

when its p-value is higher than 0.05. Therefore, the relationships between these items and

CPV, CS, CL should be removed from the model in order to achieve a better fit.

SEM_2nd

run was conducted (Figure 6.3), P-value =0.000, cmin/df = 5.915,

CFI=0.998>0.95, SRMR=0.006<0.08, RMSEA=0.041<0.06 and PCLOSE=0.991>0.05,

TLI=0.978>0.9, GFI=0.995>0.9. The model retains its excellent fit (see Appendix 6.5 for full

results)

Figure 6.3: The second SEM (SEM_2nd

run)

226

The results are summarised in the following table:

Measure CMIN/DF CFI SRMR RMSEA Pclose GFI TLI p-

value Model fit

SEM SEM_1strun 9.307 0.997 0.005 0.053 0.207 0.995 0.955 0.000

Initial SEM, then remove all relationships that are not significant

Excellent

SEM_2rdrun 5.915 0.998 0.006 0.041 0.991 0.995 0.978 0.000 Final SEM used Excellent

Threshold >0.95 <0.08 <0.06 >0.05 >0.9 >0.9 <0.001

Table 6.14: Summarising results from SEM running (SEM_1strun, SEM_2

ndrun)

The relationships between constructs relating to customer perceived value (CPV) have

been presented at table 6.15. In that, H20A, H13A, H23, H19A, H17B, H9A, H12A, H16,

H5A have shown statistically significant results as P-value was lower than 0.05, the “***” at

p-value represents for its values of lower than 0.001. Therefore, these hypotheses were

supported.

The hypotheses of H21A, H22A, H1A, H2A, H3A, H4A were not supported when its p-

values were higher than 0.05. The hypothesis of H17A is statistically significant as its p-value

was lower than 0.05 but not supported because the standardised loading was -0.113 which is

inconsistent with the hypothesis that there is a positive relationship between ESQX1 and

CPV.

In such tables, a light green colour represents “supported” result, light amber

demonstrates “supported (weak)” and mixed pink and light red will illustrate “not supported”.

Yellow presents for “significant but not supported”.

227

Hypothesis Path Standardised

loadings

P-

value Results

H20A CPV <--- PRICE 0.295 *** Supported

H13A CPV <--- ISL 0.199 *** Supported

H23 CPV <--- TRUST 0.161 *** Supported

H19A CPV <--- PROE 0.124 *** Supported

H17B CPV <--- ESQX2 0.114 *** Supported

H9A CPV <--- SWC -0.081 *** Supported (weak)

H12A CPV <--- SQ 0.061 0.019 Supported (weak)

H16 CPV <--- CUSER 0.057 0.001 Supported (weak)

H5A CPV <--- Q4 -0.041 *** Supported (weak)

H21A CPV <--- PROQ 0.036 0.142 Not supported

H22A CPV <--- CSR -0.04 0.11 Not supported

H1A CPV <--- INCOME 0 0.987 Not supported

H2A CPV <--- LOCATION 0.013 0.323 Not supported

H3A CPV <--- AGE -0.005 0.687 Not supported

H4A CPV <--- GENDER 0.001 0.962 Not supported

H17A CPV <--- ESQX1 -0.113 *** Significant but not supported

Table 6.15: Results about the relationships between customer perceived value and its

independent variables


The relationships between constructs relating to customer satisfaction (CS) have been

presented at table 6.16. In that, H7A, H13B, H12B, H14, H6, H21B, H10A, H19B, H20B,

H1B, H2B have shown statistically significant results as P-value were lower than 0.05, the

“***” at p-value represents for its values of lower than 0.001. Therefore, these hypotheses

were supported.

The hypotheses of H11A, H3B, H4B, H5B were not supported when its p-values were

higher than 0.05.

228

Hypothesis Path Standardised

loadings P-value Results

H7A CS <--- CPV 0.301 *** Supported

H13B CS <--- ISL 0.24 *** Supported

H12B CS <--- SQ 0.214 *** Supported

H14 CS <--- STIMA 0.188 *** Supported

H6 CS <--- CUEXP 0.148 *** Supported

H21B CS <--- PROQ 0.144 *** Supported

H10A CS <--- ALA -0.113 *** Supported

H9B CS <--- SWC 0.071 *** Supported (weak)

H20B CS <--- PRICE 0.051 *** Supported (weak)

H1B CS <--- INCOME 0.025 0.007 Supported (weak)

H2B CS <--- LOCATION 0.02 0.024 Supported (weak)

H11A CS <--- RBEX 0.03 0.139 Not supported

H3B CS <--- AGE 0.006 0.546 Not supported

H4B CS <--- GENDER 0.018 0.05 Not supported

H5B CS <--- Q4 0.003 0.722 Not supported

Table 6.16: Results about the relationships between customer satisfaction and its



The relationships between constructs related to customer loyalty (CL) have been

presented at table 6.17. In that, H11B, H12C, H8, H19B, H9C, H17D, H10B, , H20C, H24,

H1C have shown its statistical significantly results as P-value were lower than 0.05, the

“***” at p-value represents for its values of lower than 0.001. Therefore, these hypotheses

were supported.

The hypotheses of H7B, H22B, H21C, H5C, H2C, H3C, H4C were not supported when

its p-values were higher than 0.05. The hypotheses of H17C, H15, H18 were statistically

significant as its p-value was lower than 0.5 but not supported because the standardized

loading was -0.076, -0.069, -0.038 respectively which is inconsistent with hypothesis that

there are a positive relationship between ESQX1, STAC, LPRO and CS.

229

Hypothesis

Path Standardised

loadings

P-

value Results

H11B CL <--- RBEX 0.306 *** Supported

H12C CL <--- SQ 0.179 *** Supported

H8 CL <--- CS 0.178 *** Supported

H19B CL <--- PROE 0.141 *** Supported

H9C CL <--- SWC 0.113 *** Supported

H17D CL <--- ESQX2 0.106 *** Supported

H10B CL <--- ALA -0.101 *** Supported

H20C CL <--- PRICE 0.069 *** Supported (weak)

H24 CL <--- HABIT 0.057 *** Supported (weak)

H1C CL <--- INCOME 0.024 0.017 Supported (weak)

H7B CL <--- CPV -0.158 0.126 Not supported

H22B CL <--- CSR -0.013 0.547 Not supported

H21C CL <--- PROQ -0.015 0.474 Not supported

H5C CL <--- Q4 -0.022 0.056 Not supported

H2C CL <--- LOCATION 0.009 0.441 Not supported

H3C CL <--- AGE -0.016 0.135 Not supported

H4C CL <--- GENDER 0.009 0.4 Not supported

H17C CL <--- ESQX1 -0.076 *** Significant but not supported

H15 CL <--- STAC -0.069 *** Significant but not supported

H18 CL <--- LPRO -0.038 0.018 Significant but not supported

Table 6.17: Results about the relationships between customer loyalty and its



The results can be summarized as follows (Figure 6.9) and the number is the path

coefficients, the significant influences are black-solid lines, significant influences are black-

dash lines and yellow dash lines represent for a statistically significant result but not

supported compared with original proposed hypotheses.

230

-0.101***

0.0

57***

0.301***

0.0

61***

Having a direct effect

Having no direct effects

Significantly but not supported

Figure 6.4: The results of revised model of this research

Instore

logistics

ssss

A core e-

service

quality

Service

qauality

Customer

service

Customer

experience

Retail brand

experience

Product

quality Price

Corporate social

responsibility

Store

image

Habit

Trust

Switching

costs

Alternative

attractiveness

Loyalty

programs

ss

Promotion

effects

CUSTOMER

PERCEIVED VALUE

Store

accessibility

CUSTOMER

LOYALTY

CUSTOMER

SATISFACTION

Gender Age Strategic groups Income Location Control variables *** p<0.001, ** p<0.01, * p<0.05

Website

quality

scale

231

6.6.3.4. Multigroup analysis

Multigroup analysis is designed to investigate whether the model is the same between

groups. Prior to the structural invariance test, measurement invariance should be assessed to

determine if the model is invariant across examined groups. This test is regarded as another

type of moderation test (Hair et al., 2006). The chi-square difference test is a well-known

acceptable method for assessing measurement invariance. The chi-square test showing p-

value being higher than 0.05 means that the measurement models are invariant. This research

used the chi-square test to investigate between many groups including strategic groups

(between different supermarket business models), gender, income, age ranges, locations,

occupation and education levels. In addition, in some cases, when the chi-square test cannot

present the whole results, critical ratio (z-score) will be used to investigate differences

between groups (section 6.6.3.4.6.2 and 6.6.3.4.6.3). It should be noted that this section will

only present all statistical results about diffences across groups for factors related to customer

perceived value, customer satisfaction and customer loyalty which are fully summarised at

Appendix 7.1, 7.2, 7.3. Discussion will be presented in Chapter 7. However, based on the

objectives of this research, the researcher is only going to fully investigate and discuss

differences between groups for factors related to customer loyalty, which will be presented at

section 7.5.

6.6.3.4.1. Comparison between retail strategic groups

The following contents will present the statistical results of multigroup analysis, see

section 4.1.2 (Phase One - Section two-question 4) for understanding how supermarkets were

divided into different strategic groups (different supermarket business models). The brief

summaryg of the five main strategic Vietnamese supermarkets is demonstrated as below:

GROUP 1: The group of specilised daily consumer goods (Coopmart or BigC)

GROUP 2: The group of multipurpose premium supermarkets 1 (Lotte mart)

GROUP 3: Premium supermarket chains with convenience stores (Vinmart)

GROUP 4: The group of multipurpose supermarkets 2 (Aeon)

GROUP 5: Other supermarkets

232

Comparison between COOP or BIGC ad LOTTE MART

The model is fit with P-value =0.000, cmin/df = 3.083, CFI=0.997>0.95,


GFI=0.993>0.9. The model is fit and results are reliable.

X2 DF

Unconstrained 154.168 50

Constrained 213.898 83

P-Value 0.003

Path Name

Coopmart

or BigC

Beta

Lotte Mart

Beta

Difference in

Betas

P-Value for

Difference Interpretation

SQ → CPV. 0.062† 0.209** -0.147 0.069 The positive relationship between CPV and SQ is stronger for Lotte Mart.

ESQX2 → CL. 0.043 0.208*** -0.165 0.014 The positive relationship between CL and ESQX2 is stronger for Lotte Mart.

ALA → CL. -0.060*** -0.228*** 0.168 0.000 The negative relationship between CL and ALA is stronger for Lotte Mart.

ISL → CS. 0.208*** 0.306*** -0.098 0.079 The positive relationship between CS and ISL is stronger for Lotte Mart.

PRICE → CL. 0.061** 0.158*** -0.096 0.055 The positive relationship between CL and PRICE is stronger for Lotte Mart.

INCOME → CS. 0.011 0.084*** -0.073 0.01 The positive relationship between CS and INCOME is stronger for Lotte Mart.

PROE → CPV. 0.153*** 0.024 0.129 0.028 The positive relationship between CPV and PROE is stronger for Coopmart or BigC.

SQ → CS. 0.224*** 0.107* 0.117 0.030 The positive relationship between CS and SQ is stronger for Coopmart or BigC.

RBEX → CL. 0.326*** 0.219*** 0.107 0.088 The positive relationship between CL and RBEX is stronger for Coopmart or BigC.

STIMA → CS. 0.216*** 0.129** 0.087 0.088 The positive relationship between CS and STIMA is stronger for Coopmart or BigC.

Table 6.M.1: Multigroup analysis for COOP or BIGC ad LOTTE MART

(Source: Data analysis results from the author

Tool used from Gaskin and Lim (2018))

The p-value of the chi-square difference test is significant as p-value is 0.003 which is

lower than 0.1 (10%). Therefore, the model differs across groups.

The main differences between the two groups will present as follows. Consumers from

the group of multipurpose premium supermarkets 1 (Lotte mart) are concerned more with

service and e-service quality while consumers from the group of specilised daily consumer

goods (Coopmart or BigC) are not. In that, there is a positive and strong relationship between

service quality and customer perceived value, between e-service quality related to E-S-QUAL

and customer loyalty was found in the group of multipurpose premium supermarkets while

that relationship at the group of specilised daily consumer goods were not found.

233

The strong impact of promotion on customer perceived value of consumers from the

group of specilised daily consumer goods was not replicated among consumers from the

group of multipurpose premium supermarkets 1. The impact of service quality and store

image on customer satisfaction is stronger for the group of specilised daily consumer goods

and the level of consumers’ retail brand experience affecting customer loyalty in this group is

also higher than the group of multipurpose premium supermarkets 1.

Especially, at the group of multipurpose premium supermarkets 1, if consumers perceive

high alternative attractiveness, the level of loyalty decreases by 22.8%, while this figure of

consumers from the group of specialised daily consumer goods is only 6%. At the group of

multipurpose premium supermarkets 1, price was found to have a strong and positive impact

on customer loyalty. However, among the group of specialised daily consumer goods, price

has a low impact on customer loyalty, and it can explain only 6.1% variation in customer

loyalty.

The positive relationship between customer satisfaction and in-store logistics is stronger

for the group of multipurpose premium supermarkets 1. Income was found to have a slightly

positive influence on customer satisfaction at the group of multipurpose premium

supermarkets 1 while this relationship could not be found at the group of specialised daily

consumer goods. At the group of multipurpose premium supermarkets 1, consumers with

higher income seem to be more satisfied than consumers with lower income.

Comparison between COOP or BIGC ad VINMART




234

X2 DF



P-Value 0.006

Path Name

Coopmart

or BigC

Beta

Vinmart

Beta

Difference

in Betas

P-Value for


ESQX2 → CL. 0.043 0.159*** -0.116 0.043 The positive relationship between CL and ESQX2 is stronger for Vinmart.

PRICE → CPV. 0.263*** 0.365*** -0.102 0.015 The positive relationship between CPV and PRICE is stronger for Vinmart.

CUEXP → CS. 0.119*** 0.219*** -0.1 0.045 The positive relationship between CS and CUEXP is stronger for Vinmart.

ALA → CL. -0.060*** -0.172*** 0.113 0.001 The negative relationship between CL and ALA is stronger for Vinmart.


Table 6.M.2: Multigroup analysis for COOP or BIGC and VINMART





At the group of premium supermarket chain with convenience stores, higher perceived

alternative attractiveness decreases the loyal level, alternative attractiveness can negatively

explain 17.2 percent variation in customer loyalty, while the figure of the group of specialised

daily consumer goods is only 6 percent. This research also revealed that e-service quality

related to E-S-QUAL is one of the main indicators of customer loyalty at the group of

premium supermarket chain with convenience stores, while there was no suchrelationship

found at the group of specialised daily consumer goods.

The positive relationships between price and customer perceived value, customer

experience and customer satisfaction are stronger for the group of premium supermarket

chain with convenience stores. In contrast, the postive relationship between store image and

customer satisfaction is stronger for the group of specialised daily consumer goods.

235

Comparison between Lotte Mart and Vinmart




X2 DF



P-Value 0.1

Path Name Lotte Mart

Beta

Vinmart

Beta

Difference

in Betas

P-Value for


SQ → CPV. 0.209** -0.032 0.241 0.014 The positive relationship between CPV and SQ is stronger for Lotte Mart.

PRICE → CL. 0.158*** 0.009 0.149 0.016 The positive relationship between CL and PRICE is stronger for Lotte Mart.

CUSER → CPV. -0.008 0.119** -0.128 0.031 The positive relationship between CPV and CUSER is stronger for Vinmart.

SQ → CS. 0.107* 0.220*** -0.113 0.067 The positive relationship between CS and SQ is stronger for Vinmart.

Table 6.M.3: Multigroup analysis for Lotte Mart and Vinmart



The p-value of the chi-square difference test is not significant at 10% as p-value is much

higher than 0.1. However, there are some small differences about relationships between

constructs which should be examined.

Price was found to have no impact on customer loyalty and service quality has no

influence on customer perceived value at the group of premium supermarket chain with

convenience stores, while the above relationship was found at the group of multipurpose

premium supermarkets 1. At the group of multipurpose premium supermarkets 1, service

quality is one of the main indicators of customer perceived value and it can explain 20.9

percent variation in customer perceived value and the figure of how price influences

customer loyalty is 15.8 percent. At the group of premium supermarket chain with

convenience stores, no such relationships were found. In contrast, at the group of

multipurpose premium supermarkets 1, customer service was found having no impact on

customer perceived value while at the group of premium supermarket chain with convenience

stores, customer service can describe 11.9 percent variation in customer perceived value. The

final difference between these two groups is the effect of service quality on customer

satisfaction which is strongest for the group of premium supermarket chains with

convenience stores.

236

Comparison between COOP or BIGC and AEON




X2 DF



P-Value 0.096

Path Name

Coopmart

or BigC

Beta

Aeon Beta Difference

in Betas

P-Value

for

Difference

Interpretation

PROE → CL. 0.170*** 0.019 0.151 0.034 The positive relationship between CL and PROE is stronger for Coopmart or BigC.

ESQX2 → CL. 0.043 0.173* -0.13 0.094 The positive relationship between CL and ESQX2 is stronger for Aeon.

TRUST → CPV. 0.130*** 0.278*** -0.148 0.063 The positive relationship between CPV and TRUST is stronger for Aeon.

ALA → CS. -0.105*** -0.173*** 0.067 0.065 The negative relationship between CS and ALA is stronger for Aeon.

SQ → CS. 0.224*** 0.323*** -0.099 0.055 The positive relationship between CS and SQ is stronger for Aeon.

PROQ → CS. 0.119*** 0.300*** 0.181 0.006 The positive relationship between CS and PROQ is stronger for Aeon.

Table 6.M.4: Multigroup analysis for COOP or BIGC and AEON



The p-value of the chi-square difference test is significant as p-value is 0.096 which


Promotion is one of the main indicators of customer loyalty at the group of specialised

daily consumer goods but no above impact was found at the group of multipurpose

supermarkets 2. In contrast, e-service quality related to E-S-QUAL can positively describe

17.3 percent variation in customer loyalty at the group of multipurpose supermarkets 2 but it

has no effect on customer loyalty at the group of specialised daily consumer goods. The

positive relationship between trust and customer peceived value, alternative

attractiveness/service quality/product quality and customer satisfaction is stronger for the

group of multipurpose supermarkets 2.

6.6.3.4.2. Comparison between gender




237

X2 DF



P-Value 0.02

Path Name MALE

Beta

FEMALE

Beta

Difference

in Betas

P-Value for


PRICE → CPV. 0.220*** 0.326*** -0.105 0.039 The positive relationship between CPV and PRICE is stronger for FEMALE.

ALA → CS. -0.139*** -0.102*** -0.037 0.054 The negative relationship between CS and ALA is stronger for MALE.

PROE → CL. 0.212*** 0.110*** 0.102 0.032 The positive relationship between CL and PROE is stronger for MALE.

Table 6.M.5: Multigroup analysis for gender





Detailed investigation of the relationship between constructs of male and female was

conducted. The main differences between female and male perceptions are presented as

follows. That the positive relationship between price and customer perceived value is

stronger for females means that their perceived value is strongly affected by price; the

influence level is weaker for male. The negative relationship between alternative

attractiveness and customer satisfaction is stronger for males. Higher perceived alternative

attractiveness leads to reductions in the level of satisfaction and this relationship is weaker for

females. Another result relating to gender-group comparison is that the positive relationship

between promotion and customer loyalty is stronger for males. It means that promotion

effects lead to stronger loyalty behaviour for males where promotion can explain 21.2 % in

variation of customer loyalty while that for females is 11%.

6.6.3.4.3. Comparison between income groups

Based on the market where the data for research was collected income which is lesthan 5

million VND (GB£170) is considered “low”; income from 5 to 10 million VND (GB£170-

340) is considered “medium”; income from 10-20 million VND (GB£340-680) is considered

“medium-high”, and income from 20-50 million VND (GB£680-1700GBP) is considered

“high” (Based on comments of the retailing expert Pham Xuan Lan, who is an associate

238

professor at University of Economics Ho Chi Minh City in Vietnam, collected at Phase One

in this research,)

Comparison between income of “under 5 million VND (GB£170GB)” and “from 5 to 10

million VND (GB£170-340 GBP)” groups




X2 DF



P-Value 0.000

Path Name

Under 5

million VND

Beta

From 5-10

million

VND Beta

Difference

in Betas

P-Value

for

Difference

Interpretation

SQ → CPV. 0.006 0.156** -0.15 0.016 The positive relationship between CPV and SQ is stronger for From 5-10 million VND.

CUSER → CPV. 0.035 0.106*** -0.072 0.086 The positive relationship between CPV and CUSER is stronger for From 5-10 million VND.

PRICE → CPV. 0.351*** 0.189*** 0.162 0.000 The positive relationship between CPV and PRICE is stronger for Under 5 million VND.

CPV → CS. 0.287*** 0.346*** -0.058 0.057 The positive relationship between CS and CPV is stronger for From 5-10 million VND.

STIMA → CS. 0.238*** 0.121*** 0.117 0.007 The positive relationship between CS and STIMA is stronger for Under 5 million VND.

SQ → CL. 0.131*** 0.284*** -0.154 0.011 The positive relationship between CL and SQ is stronger for From 5-10 million VND.

PRICE → CL. 0.111*** -0.029 0.139 0.001 The positive relationship between CL and PRICE is stronger for Under 5 million VND.

Table 6.M.6: Multigroup analysis for “under 5 million VND (GB£170)” and “from 5 to

10 million VND (GB£170-340)” income groups





The above results show that service quality which relates to how service employees treat

their consumers and customer service only influence customer perceived value in a medium

income group; while with low income consumers (under GB£170 per month), the

relationship between service quality and customer service on customer perceived value was

not supported. Besides that, price has a strong and positive impact on customer perceived

value among low income consumers, with the influence level decreasing among medium

income group. In particular, price can explain 35.1 % variation of customer perceived value

in low income groups, while with an average income group, the figure is 18.9%.

239

At low income, service quality can explain 13.1 % in variation of customer loyalty,

while the figure for the medium income group is 28.4 %. Consumers with medium incomes

consider that service quality is one of the main indicators of their loyalty behaviour. The

results also revealed that low income groups consider price is one of the main factors

affecting their loyalty behaviour but price has no effect on customer loyalty in medium

income groups. The positive relationship between store image and customer satisfaction is

stronger for the group of low income consumers while the relationship between customer

perceived value and customer satisfaction is stronger for the group of medium income

consumers.

Comparison between income of “under 5 million VND (GB£170)” and “from 10 to 20

million VND (GB£340-680)” groups




X2 DF



P-Value 0.304

Path Name

Under 5

million VND

Beta

From 10-20

million VND

Beta

Difference

in Betas

P-Value

for

Difference

Interpretation

ISL → CS. 0.262*** 0.145*** 0.117 0.013 The positive relationship between CS and ISL is stronger for Under 5 million VND.

SQ → CS. 0.183*** 0.282*** -0.099 0.063 The positive relationship between CS and SQ is stronger for From 10-20 million VND.

Table 6.M.7: Multigroup analysis for “under 5 million VND (GB£170)” and “from 10 to

20 million VND (GB£340-680)” income groups





constructs which should be examined. The results show that the level of service quality

affecting customer satisfaction is higher for the group of medium-high income consumers,

service quality can explain 28.2% variation of customer satisfaction at medium-high income

consumers while that of low income consumers is 18.3%. In-store logistics have a stronger

impact on customer satisfaction at the group of low income consumers.

240

6.6.3.4.4. Comparison between location

Between Ho Chi Minh and Hanoi




X2 DF



P-Value 0.138

Path Name HCM

Beta

Hanoi

Beta

Difference

in Betas

P-Value for


PRICE → CPV. 0.213*** 0.377*** -0.164 0.002 The positive relationship between CPV and PRICE is stronger for Hanoi.

ISL → CS. 0.172*** 0.277*** -0.105 0.053 The positive relationship between CS and ISL is stronger for Hanoi.

HABIT → CL. 0.108*** 0.034 0.074 0.091 The positive relationship between CL and HABIT is stronger for HCM.

RBEX → CL. 0.238*** 0.352*** -0.115 0.05 The positive relationship between CL and RBEX is stronger for Hanoi.

ESQX2 → CL. 0.158*** 0.063 0.095 0.089 The positive relationship between CL and ESQX2 is stronger for HCM.

Table 6.M.8: Multigroup analysis for Ho Chi Minh and Hanoi





constructs which should be examined. Based on the statistical results, the positive

relationship between price and customer perceived value is stronger in Hanoi. It showed that

supermarket consumers in Hanoi are concerned more about price and price can explain 37.7

percent variation in customer perceived value in Hanoi while that in Ho Chi Minh is 21.3

percent. That the positive relationship between in-store logistics and customer satisfation is

stronger for Hanoi means that consumers in Hanoi consider in-store logistic to be one of the

important indicators of satisfaction, while the relationship between ISL and CS in Ho Chi

Minh is weaker. In this research, habit and e-service quality related to E-S-QUAL were found

to have a strong and positive impact on customer loyalty for consumers from Ho Chi Minh.

However, in Hanoi, habit and e-service quality related to E-S-QUAL was found not to have

arelationship with customer loyalty.

The level of retail brand experience (RBEX) affects customer loyalty is different across

locations, in Hanoi, RBEX can describe 35.2 percent variation in customer loyalty but that of

Ho Chi Minh is only 23.8 percent.

241

Between Ho Chi Minh and Da Nang




X2 DF



P-Value 0.009

Path Name HCM

Beta

Da Nang

Beta

Difference

in Betas

P-Value for


PRICE → CPV. 0.213*** 0.363*** -0.15 0.027 The positive relationship between CPV and PRICE is stronger for Da Nang.

SQ → CL. 0.268*** 0.099 0.169 0.045 The positive relationship between CL and SQ is stronger for HCM.

Table 6.M.9: Multigroup analysis for Ho Chi Minh and Da Nang





In Ho Chi Minh, service quality was found to have a strong and positive impact on

customer loyalty. However, there was no such relationship in the case of Da Nang. That price

positively affects customer perceived value is stronger in Da Nang means that consumers

from Da Nang are more sensitive about price than consumers in Ho Chi Minh; price can

explain 36.3 percent variation in customer perceived value in Da Nang while the figure for

Ho Chi Minh is only 21.3 percent.

Between Can Tho and Binh Duong




242

X

2 DF



P-Value 0.003

Path Name Can Tho

Beta

Binh Duong

Beta

Difference

in Betas

P-Value for


ALA → CS. -0.091*** -0.129*** 0.038 0.069 The negative relationship between CS and ALA is stronger for Binh Duong.

SQ → CS. 0.145*** 0.257*** -0.112 0.04 The positive relationship between CS and SQ is stronger for Binh Duong.

Table 6.M.10: Multigroup analysis for Can Tho and Binh Duong





There are two main differences between Can Tho and Binh Duong: service quality has a

stronger positive influence on customer satisfaction in Binh Duong - 25.7 percent variation in

customer satisfaction in Binh Duong and only 14.5 percent in Can Tho. The negative

relationship between alternative attractiveness and customer satisfaction is stronger for Binh

Duong with significantly reducing satisfaction levels while the level at Can Tho is lower,

where alternative attractiveness can negatively explain 9.1 percent variation in customer

satisfaction.

6.6.3.4.5. Comparison between age groups

Comparison between 18-22 and 22-30




243

X2 DF



P-Value 0.022

Table 6.M.11: Multigroup analysis for “18-22 and 22-30” age groups



The p-value of the chi-square difference test is significant when p-value of 0.022 is lower

than 0.1 (10%). Therefore, the model differs across groups. Customer service and service

quality were found to have a strong positive influence on customer perceived value among

the group of 23-30 year-olds. However, a similar relationship could not be found among the

group of 18-22 year-olds. Consumers of lower ages areconcerned more about price and store

image while consumers of older age groups are concerned more about service quality and

promotions. The positive relationship between trust and customer perceived value is stronger

for 18-22 year-old consumers.

Comparison between 22-30 and above 55 year-old groups




Path Name 18-22

Beta

23-30

Beta

Difference

in Betas

P-Value for


CUSER → CPV. 0.027 0.113** -0.086 0.074 The positive relationship between CPV and CUSER is stronger for 23-30.

PRICE → CPV. 0.360*** 0.189*** 0.171 0.002 The positive relationship between CPV and PRICE is stronger for 18-22.

PROE → CPV. 0.082** 0.196*** -0.114 0.037 The positive relationship between CPV and PROE is stronger for 23-30.

TRUST → CPV. 0.206*** 0.104* 0.103 0.08 The positive relationship between CPV and TRUST is stronger for 18-22.

SQ → CPV. 0.000 0.180** -0.179 0.013 The positive relationship between CPV and SQ is stronger for 23-30.

STIMA → CS. 0.206*** 0.109** 0.097 0.069 The positive relationship between CS and STIMA is stronger for 18-22.

SQ → CL. 0.105** 0.229*** -0.124 0.071 The positive relationship between CL and SQ is stronger for 23-30.

244

X2 DF



P-Value 0.121

Path Name 23-30

Beta

above 55

Beta

Difference

in Betas

P-Value

for

Difference

Interpretation

SQ → CPV. 0.180** -0.008 0.188 0.046 The positive relationship between CPV and SQ is stronger for 23-30.

STIMA → CS. 0.109** 0.217*** -0.108 0.067 The positive relationship between CS and STIMA is stronger for above 55.

SWC → CS. 0.059* 0.148*** -0.088 0.014 The positive relationship between CS and SWC is stronger for above 55.

SWC → CL. 0.117*** 0.234*** -0.117 0.011 The positive relationship between CL and SWC is stronger for above 55.

Table 6.M.12: Multigroup analysis for “22-30 and above 55” age groups



The p-value of the chi-square difference test is not significant at 10% as p-value is higher

than 0.1. However, there are some small differences about relationships between constructs

which should be examined. The above results show that there is no relationship between

service quality and customer perceived value to be found in the group of consumers who are

over 55, while service quality can explain 18 percent variation in customer perceived value

among the group of consumers who are 23-30 years old. Store image in the group of over 55s

was found to have a positive and stronger impact on customer satisfaction than that of the

group of 23-30 year-olds. The positive relationship between switching cost and customer

loyalty is stronger for the group of over 55s; loyal consumers with higher perceived switching

cost will continue to be loyal and at the group of over 55s, switching cost can explain 23.4

percent variation in customer loyalty while that of the group of 23-30 year-olds is only 11.7

percent. The positive relationship between switching costs and customer satisfaction is

stronger for the group of over 55s. Consumers with higher perceived switching cost will

remain to be satisfied and among the over 55s, switching cost can explain 14.8 percent

variation in customer satisfaction while that of the 23-30 year-olds is only 5.9 percent.

Comparison between 18-22 and 41-55




245

X

2 DF



P-Value 0.124

Path Name 18-22

Beta

41-55

Beta

Difference

in Betas

P-Value for


TRUST → CPV. 0.206*** 0.061 0.145 0.070 The positive relationship between CPV and TRUST is stronger for 18-22.

CS → CL. 0.304*** 0.023 0.281 0.063 The positive relationship between CL and CS is stronger for 18-22.

SWC → CL. 0.090*** -0.001 0.091 0.092 The positive relationship between CL and SWC is stronger for 18-22.

SQ → CPV. 0.000 0.198* -0.198 0.041 The positive relationship between CPV and SQ is stronger for 41-55.

PROE → CL. 0.112*** 0.390*** -0.278 0.001 The positive relationship between CL and PROE is stronger for 41-55.

PRICE → CL. 0.050* 0.160* -0.109 0.076 The positive relationship between CL and PRICE is stronger for 41-55.

SQ → CL. 0.105** 0.295** -0.190 0.061 The positive relationship between CL and SQ is stronger for 41-55.






constructs which should be examined. The postive relationships between trust and customer

perceived value, customer satisfaction and customer loyalty, switching costs and customer

loyalty are only significant among the group of 18-22 year-olds. Among the 41-55 year-olds,

customer satisaction was found to have no relationship with customer loyalty; trust has no

impact on customer perceived value, and switching costs do not affect customer loyalty. In

contrast, service quality was found to have no impact on customer perceived value among 18-

22 year-olds while it singificantly influences customer perceived value among 441-55 year-

olds. The positive relationships between promotion/price/service quality and customer loyalty

are much stronger for 41-55 year-olds.

Comparison between “23-30 and 31-40” age groups




246

X2 DF



P-Value 0.038

Path Name 31-40

Beta 23-30 Beta

Difference

in Betas

P-Value for


SWC → CPV. -0.015 -0.123*** 0.107 0.046 The negative relationship between CPV and SWC is stronger for 23-30.

CPV → CS. 0.214*** 0.327*** -0.112 0.03 The positive relationship between CS and CPV is stronger for 23-30.

PRICE → CL. -0.051 0.084* -0.135 0.02 The positive relationship between CL and PRICE is stronger for 23-30.

ESQX2 → CL. -0.017 0.120** -0.137 0.089 The positive relationship between CL and ESQX2 is stronger for 23-30.





than 0.1 (10%). Therefore, the model differs across groups. The relationships between e-

service quality related to E-S-QUAL/price and customer loyalty, switching costs and

customer perceived value are only supported among23-30s. Price and e-service quality

relating to E-S-QUAL have no effect on customer loyalty and switching costs have no impact

on customer perceived value among 31-40 year-olds. The positive relationship between

customer perceived value and customer satisfaction is stronger for the group of 23-30 year-

old consumers.

6.6.3.4.6. Comparison between occupation

Comparison between housewife and office staffs




247

X2 DF



P-Value 0.169

Table 6.M.15: Multigroup analysis for “housewife and office staffs” occupation groups





which should be examined. Service quality and habit was found to have a postive impact on

customer perceived value among the group of office staff while service quality and habit was

found having no influence on customer perceived value among the group of housewives.

Housewives are more sensitive about price compared to office staff; price can describe 31.2

percent variation in customer perceived value among the group of housewives while that of

office-staff is only 20%.

Comparison between students and self employment

In this analysis, some errors occurred; the researcher could not find p-value for

difference between the two groups. Therefore, additional z-score based on critical ratios were

examined to investigate differences between constructs. The results are shown as follows:

The model is fit with P-value =0.000, cmin/df = 2.402, CFI=0.996>0.95, SRMR=0.007<0.08,

RMSEA=0.036<0.06 and PCLOSE=0.999>0.05, TLI=0.966>0.9, GFI=0.990>0.9. The model

is fit and results are reliable.

Path Name Housewife

Beta

Office

staffs Beta

Difference

in Betas

P-Value for


PRICE → CPV. 0.312*** 0.200*** 0.112 0.04 The positive relationship between CPV and PRICE is stronger for Housewife.

SQ → CPV. 0.026 0.153** -0.127 0.095 The positive relationship between CPV and SQ is stronger for Office staffs.

HABIT → CL. 0.024 0.105*** -0.081 0.052 The positive relationship between CL and HABIT is stronger for Office staffs.

248

X2 DF



P-Value 0.065

Path Name Students

Beta

Self

employment

Beta

Difference

in Betas

P-Value for

Difference z-score

STIMA → CS. 0.231*** 0.068 0.164 NaN -2.318**

PROQ → CS. 0.157*** 0.008 -0.165 NaN 2.137**

RBEX → CL. 0.332*** 0.152* 0.18 NaN -2.365**

Notes: *** p-value < 0.01; ** p-value < 0.05; * p-value < 0.10

Table 6.M.16: Multigroup analysis for “students and self employment” occupation

groups




than 0.1 (10%). Therefore, the model differs across groups. The positive impact between

store image and product quality on customer satisfaction is only for the group of student

consumers. For the group of self employed consumers, the positive relationships between

store image/product quality and customer sastisfaction were not supported. Besides that, the

positive relationship between retail brand experience and customer loyalty is stronger for the

group of student consumers.

Comparison between self employed and office staff

At this analysis, some errors occurred; the researcher could not find p-value for

difference between the two groups. Therefore, additional z-score based on critical ratio were

examined to investigate differences between constructs. The results are shown as follow: The

model is fit with P-value =0.000, cmin/df = 2.276, CFI=0.997>0.95, SRMR=0.007<0.08,

RMSEA=0.0376<0.06 and PCLOSE=0.994>0.05, TLI=0.968>0.9, GFI=0.994>0.9. The

model is fit and results are reliable.

249

X2 DF



P-Value 0.227

Path Name Self employment

Beta

Office

staffs Beta

Difference in

Betas

P-Value for

Difference z-score

PROQ → CS. 0.008 0.119*** 0.127 NaN -1.768*

RBEX → CL. 0.152* 0.321*** -0.169 NaN 2.301**

Table 6.M.17: Multigroup analysis for “self employment and office staffs” occupation

groups





which should be examined. The positive relationships between product quality and customer

satisfaction only presents for the group of office staff. There is no relationship between

product quality and customer satisfaction among the group of self employmed. In addtion, the

positive relationship between retail brand experience and customer loyalty is stronger for the

group of office staff.

6.6.3.4.7. Comparison between education levels

Comparison between “A levels and college, university” groups




250

X2 DF



P-Value 0.175

Table 6.M.18: Multigroup analysis for “A levels and college, university” groups





which should be examined. The relationship between customer satisfaction and customer

loyalty; trust and customer perceived value is much stronger for the group of college and

undergraduate consumers.

Comparison between “GCSE’s and college, university” groups




X2 DF



P-Value 0.001

Path Name GCSE’s Beta College-U

Beta

Difference

in Betas

P-Value

for

Difference

Interpretation

ESQX1 → CL. -0.150** 0.128* -0.277 0.000 The relationship between CL and ESQX1 is negative for GCSE’s and positive for College-

U.

Table 6.M.19: Multigroup analysis for “GCSE’s and college, university” groups



Path Name A levels

Beta

College+

U Beta

Difference

in Betas

P-Value

for

Difference

Interpretation

TRUST → CPV. 0.172*** 0.343*** -0.171 0.056 The positive relationship between CPV and TRUST is stronger for College+ U.

CS → CL. 0.145** 0.406** -0.262 0.097 The positive relationship between CL and CS is stronger for College+ U.

251


than 0.1 (10%). Therefore, the model differs across groups. The relationship between e-

service quality related to W-S-QUAL and customer loyalty is negative for the GCSE’s group

of consumers and positive for college and undergraduate group of consumers.

6.6.3.5. Conclusion

This chapter presented a construct validation and hypothesis testing results and answered

the research questions. In that, all constructs remaining had no problem with covergent and

discriminant validity and achieved a high level of reliability. The direct relationships between

constructs have also been investigated. In addition, multigroup analysis was conducted in

order to investigate where factors affecting customer loyalty, customer satisfaction, and

customer perceived value are different across groups of supermarket business models

(strategic groups), income, location, age ranges, gender, and occupation. Full statistical

results can be seen at Appendix 6.3 and Appendix 7.1, 7.2 and 7.3. The next chapter is going

to discuss these findings.

252

Chapter 7: Discussion of the findings

7.1. Introduction

This chapter is going to discuss all research findings based on statistical tests found in

previous chapters. Results of direct effects related to customer perceived value, customer

satisfaction, customer loyalty will be presented first, followed by multigroup analysis. Then,

general discussion between all constructs will also be demonstrated.

7.2. Direct effects’ discussion

7.2.1. Results from all hypotheses related to customer perceived value (CPV)

In the retailing context, there are five main factors constituting customer perceived value,

including Price, In-store logistics, Trust, Promotion and E-service quality related to E-S-

QUAL. These factors positively affect customer perceived value. Besides that, switching

costs are also considered, higher switching costs can slightly decrease customer perceived

value to some extent. A good quality service related to in-store employees’ knowledge and

attitudes to consumers and customer service leads to quick checkout time (no waiting and

quick transactions conducted) and also contributes to higher customer perceived value.

However, the level of impact of these three factors (switching costs, service quality and

customer service) on customer perceived value is lower compared to the first five indicators

presented above. Besides that, in the Vietnamese retail market, strategic groups (different

supermarket business models) are affecting the level of customer perceived value as well.

The following part will demonstrate and investigate all constructs having a direct effect

on customer perceived value in detail. Based on the statistical results, factors having the most

important impact on customer perceived value will be presented first.

253

Dependent

variable Hypotheses Constructs Loadings

CPV

H20A 1 PRICE 0.295

H13A 2 ISL 0.199

H25 3 TRUST 0.161

H19A 4 PROE 0.124

H17B 5 ESQX2 0.114

H9A 6 SWC -0.081

H12A 7 SQ 0.061

H16 8 CUSER 0.057

H5A 9 Q4 -0.041

H21A

PROQ

Not

supported

H22A CSR

H1A INCOME

H2A LOCATION

H3A AGE

H4A GENDER

H17A ESQX1

Table 7.1: Factors directly affecting customer perceived value

According to the statistical testing results, H20A was supported, good price offered

positively affects customer perceived value (0.295). This finding is consistent with the study

of Jiang et al. (2018) and Lloyd and Luk (2010) where they found price has a positive impact

on customer perceived value. It must be noted that the results do not mean that when products

price increases, customers will have a higher perceived value. In this context, there are 3

reliable items used for a “price” construct, including “Good at this store are reasonably

priced”, “The prices of the products in this supermarket are cheaper than others”, and “Goods

at this store offer value for money”. Therefore, the finding means that the more prices offer a

reasonable value, the higher customer perceived value will be. The investigated structural

model revealed that price is the most important factor affecting customer perceived value in

the retail context. Again, this finding is similar with Lloyd and Luk (2010) as they listed price

at the top three drivers of customer perceived value.

That H13A was supported means in-store logistics have a strong and positive effect on

customer perceived value (0.199). In previous studies, there was no research on how in-store

logistics affect customer perceived value; a majority of research only investigated the

relationship between in-store logistics and customer satisfaction. In this retail context, in-

store logistics are built by three main variables which relate to how well-stocked shelves are,

the lack of problems when returning merchandise to stores and sufficient shopping carts

being offered. Compared to other factors influencing customer perceived value, in-store

logistics is in second position with a high loading of 0.199. This means that changes in in-

254

store logistics can explain 19.9 percent of changes in the value of how consumers’

perceptions are. Therefore, in order to achieve a higher perceived behaviour from consumers,

firms should invest more in their in-store logistics activities.

Trust was found to have a positive effect on customer perceived value (0.161) (H25 was

supported). This relationship is significantly strong and positioned in third place in all

possible factors affecting customer perceived value. This result shows that when consumers

trust retailers, their perceived values are definitely high. The “trust” construct was built by

three items, including “I trust this retailer”, “I consider that to shop in the stores of this

retailer is a guarantee”, and “I believe that this retailer is honest/sincere towards its

consumers”. Based on the scales, consumers appreciate more how the retailer treats them and

that leads them to believe shopping in the store is always guaranteed. This finding is

consistent with some previous studies, such as Walter and Ritter (2003) and Ponte et al.

(2015), who found that trust enhances customer perceived value by reducing non-monetary

costs perception (such as the effort and time consumers take to find their appropriate

providers). However, in this study, trust was found to have no direct relationship with

customer satisfaction and loyalty, but that indirect relationships existed (). This finding is

inconsistent with some previous studies, such as Lin et al. (2011), Martinez and Rodriguez

del Bosque (2013), Rasheed and Abadi found that there is a positive relationship between

trust and loyalty. In particular, Rasheed and Abadi stated that 35.3 percent of variation in

customer loyalty can be explained by trust while Ningsih and Segoro (2014:1018) stated “if

trust in the brand increased for one unit then the customer loyalty would increase for 0.114

points, assuming other independent variable value is fixed”.

That H19A was supported means that promotions positively affect customer perceived

value (0.124). In this research, the “promotion” construct is considered as one of the main

drivers of customer perceived value. The more promotion activities are offered, the higher

customer perceived value is. As presented in the literature review, a majority of research has

investigated how promotion influences customer loyalty but left the relationship between

promotion and customer perceived value under-researched. These results contribute how

customer perceived value is constituted in the retail context. It can be explained as follows:

when consumers notice promotion activities from a supermarket that are beneficial for them

during a shopping trip, they are more likely to perceive higher values about that supermarket.

255

Regarding e-service quality, after EFA step, in this research e-service quality was

divided into two areas as mentioned in the review part: e-service quality about website

quality scale (W-S-QUAL) and about a core e-service quality scale (E-S-QUAL). However,

only H17B (of e-service quality related to E-S-QUAL having a significant positive effect on

customer perceived value) was supported and its statistical p-value is lower than 0.05 and the

loading is 0.114. This finding is consistent with the studies of Yun and Good (2007), and

Chang and Wang (2011) who found that e-service quality has a significant positive effect on

customer perceived value. As presented in the literature review part, this construct related to

reliability, fulfillment, efficiency and privacy/security; higher e-service quality about these

terms will lead to higher perceived customer value. In the retail context, e-service quality (E-

S-QUAL) is considered one of the main drivers of customer perceived value. The H17A (E-

service quality about website (website quality scale: W-S-QUAL) has a significant positive

effect on customer perceived value) was statistically significant but not supported with the

loading of -0.113. In this research, website quality scale was found to have a significant

negative impact on customer perceived value. This is an unexpected result. There are three

main items used to measure this construct, including “Organisation’s site loads its pages fast

and easy”, “Organisation’s site enables me to complete a transaction quickly”, “Organisation

presents guarantee and privacy policy on its site”. Based on the statistical result, customer

perceived value is high even though E-S-QUAL decreases. It contradicts the theory where the

high e-service quality related to websites leads to higher customer perceived value. It means

that e-service quality related to websites cannot explain consumers’ perceptions. In this case,

low e-service quality related to websites in parallel with high e-service quality related to E-S-

QUAL is possibly creating a higher customer perceived value.

That H9A was supported means that switching costs have a negative effect on customer

perceived value (-0.081). It can be noted that there has been no previous research on how

switching costs influence customer perceived value. This research indicates that even the

relationship between these two constructs is weak but increasing switching costs will lead to

lower customer perceived value. This can be explained as follows: consumers might claim

that they are stuck in their current supermarkets’ clutches and the possibility of moving to

other supermarkets is relatively low because of high switching costs. As a result, their

perceived values toward a current chosen supermarket are more likely to decrease.

256

That H12A was supported means that there is a positive relationship between service

quality and customer perceived value (0.061). The finding is compatible with previous

studies, Rasheed and Abadi (2014), Malik (2012) and Jiang et al. (2018) which showed that

service quality has a direct and positive impact on customer perceived value. In this research,

service quality mostly related to in-store staff knowledge and attitudes toward consumers, but

the positive relationship between service quality and customer perceived value is not as high

as expected. Compared to other main drivers of customer perceived value, in-store

employees’ knowledge and behaviour explains just 6.1 percent of customer perceived value,

while Rasheed and Abadi (2014:303) stated that “32.6 percent of variation in perceived value

can be described by service quality”. In addition, Lloyd and Luk (2010) listed service quality

in the list of the top three drivers of customer perceived value. In Jiang et al. (2018), service

quality is the most important indicator of customer perceived value. With the comprehensive

research conducted, the findings of this research can be reliable, indicating that service

quality is not considered to be one of the main drivers of customer perceived value. However,

it is one of the main indicators of customer satisfaction and customer loyalty.

That H16 was supported means that higher customer service, the better customer

perceived value (0.057). The finding is consistent with the study of Mangnale and Chavan

(2012) who indicated that customer service has a positive impact on customer perceived

value. In this research, customer service does not have a strong effect on customer perceived

value and customer service can explain 5.7 percent of variation in customer perceived value.

There are only 2 remaining main items used to measure customer service in this research (see

Appendix 5.10), including “having a short waiting time at the checkouts”, “doing faster

transactions without waiting customers”. The finding demonstrates that customer perceived

value will be higher if there are short checkouts times and transactions are completed faster.

However, if compared to other antecedents of customer perceived value, the customer service

effects are not so powerful. The above result is also consistent with Kursunluoglu’s study

(2014).

That H5A was supported means that people who choose different groups of supermarkets

for shopping have different customer perceived value. In this research, “Q4” qualitative

variable covers supermarkets where consumers usually choose to shop (different supermarket

business models), 1 was coded for “Cooopmart and BigC”, 2 was “Lotte Mart”, 3 was

“Vinmart”, 4 was “Aeon”, and 5 was “other supermarkets”. That the loading value is -0.041

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means that the higher choice of Q4, the lower customer perceived value is. In other words,

consumers who choose to shop at Coopmart or BigC, Lotte Mart and Vinmart will have a

higher perceived value compared to that of Aeon or other supermarkets in general.

According to the test results, H21A (Good product quality is positively associated with

customer perceived value) was not statistically significant or supported. This finding is

inconsistent with previous research where Jiang et al. (2018) found a positive relationship

between product quality and customer perceived value; Lloyd and Luk (2010) found that

product quality is in the list of the top three drivers of customer perceived value. In general,

this research shows that higher product quality will lead to increases in the level of customer

satisfaction (see section 7.2.2). In addition, there was no relationship found between

corporate social responsibility and customer perceived value (H22A). According to the

statistical testing results, H1A, H2A, H3A, H4A (income has an effect on customer perceived

value, location where people stay has an effect on customer perceived value, age range

affects customer perceived value, Gender affects customer perceived value) were not

supported. These variables are not statistically found to have an affect on customer perceived

value.

7.2.2. Results from all hypotheses related to customer satisfaction (CS)

There are 7 main factors directly influencing customer satisfaction in the retailing

industry, which will be named in decreasing order of importance: customer perceived value,

in-store logistics, service quality related to in-store employees’ knowledge and attitudes

toward consumers, store image, customer experience, product quality and alternative

attractiveness. Besides that, switching costs and price also have a relatively slight direct

impact on customer satisfaction. Considering qualitative variables, income and the location in

which consumers stay slightly affects a satisfied behaviour. The results show that people with

higher income seem to be more satisfied; supermarkets’ consumers in Ho Chi Minh, Binh

Duong and Can Tho are more satisfied compared to those of Ha Noi and Da Nang. Retail

brand experience was found not to have a relationship with customer satisfaction in this

study. In addition, age range, gender and strategic groups also do not influence customer

satisfaction.

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This following part will demonstrate and investigate all constructs having a direct effect

on customer satisfaction in detail. Based on the statistical results, factors having the most

important impact on customer satisfaction will be presented first.

Dependent


CS

H7A 1 CPV 0.301

H13B 2 ISL 0.239

H12B 3 SQ 0.214

H14 4 STIMA 0.188

H6 5 CUEX 0.148

H21B 6 PROQ 0.144

H10A 7 ALA -0.113

H9B 8 SWC 0.071

H20B 9 PRICE 0.051

H1B 10 INCOME 0.025

H2B 11 LOCATION 0.02

H11A

RBEX

Not

supported

H3B AGE

H4B GENDER

H5B Q4

Table 7.2: Factors directly affecting customer satisfaction

According to the statistical test results, H7A was supported, customer perceived value

has a positive influence on customer satisfaction (0.301). In this study, customer perceived

value is measured by three main reliable and validated items, including “Prices are fair”,

“Products are worthwhile”, and “Compared to the price we pay, we get a reasonable quality”.

It is clearly proved that customer perceived value can explain 30.1 percent of changes in

customer satisfaction. This is the strongest factor affecting customer satisfaction. The result

implies that those who perceive high values will be more likely to be satisfied with a

supermarket. This finding is consistent with previous studies, El-Adly and Eid (2016), Babin

et al. (2007), Chebat et al. (2014), Johnes et al. (2006), Zameer et al. (2015), Chen and Tsai

(2008), Ryu et al. (2008), Sands et al. (2015), Walsh et al. (2011), Cronin et al. (2000), Brady

et al. (2005), Mangnale and Chavan (2012), Lin and Wang (2006), Tung (2004), where they

confirmed that customer perceived value is one of the antecedents of customer satisfaction.

The research shows that higher consumer perceived value will lead to higher levels of

satisfaction.

That H13B was supported means that in-store logistics have a strong and positive effect

on customer satisfaction (with high loading of 0.239). This finding is consistent with some

previous studies where Bouzaabia et al. (2013), Samili et al. (2005), Arnold et al. (2005),

Ltifi and Gharbi (2015), Mou et al. (2017) found that in-store logistics can be instrumental in

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helping customers navigate the retail servicescape efficiently and effectively, thereby

improving customer experience and satisfaction; and the future patronage intention would be

adversely affected were customers to experience the consequences of inadequate in-store

logistics. The scale of in-store logistics in this study is built by three reliable items and

proved its validity via CFA: “In this supermarket, the shelves are well-stocked”, “no

problems when returning merchandise”, and “in this supermarket, there are enough shopping

carts”. In-store logistics is the second strongest factor affecting customer satisfaction (0.239),

the first place is customer perceived value with loading of 0.301. It is clear that the better in-

store logistics provided will lead to higher levels of customer satisfaction because consumers

can more easily find and return products to shelves, while products always being available

during consumers’ shopping process can improve consumer experience and make them

happier.

H12B was supported, demonstrating there is a positive relationship between service

quality and customer satisfaction (0.214). This finding is consistent with Cronin et al. (2000),

Dauda and Lee (2016), Kim et al. (2004), Hsieh and Hiang (2004), Liu et al. (2011), Sivadas

and Baker-Prewitt (2000), Chang and Yeh (2017) who found there is a strong positive

relationship between service quality and customer satisfaction, while the studies from Bauer

et al. (2006), Turel and Serenko (2006) and Wang et al. (2004), Hsu (2006), Zameer et al.

(2015), Szwarc (2005); Baki et al. (2009) stated that service quality is a vital element in

creating and increasing customer satisfaction, and more and more firms have stated that high

customer satisfaction can be traced back to good service quality (Szwarc, 2005). Kitapci et al.

(2013) examined the effects of specific dimensions of service quality on satisfaction in

supermarkets, and found that “independent variables together describe 56 percent of customer

satisfaction variability” (Kitapci et al., 2013:248). The above conclusion is slightly at odds

with findings of this research, where service quality related to in-store staff knowledge and

attitudes toward consumers can explain 21.4 percent of variation in customer satisfaction if

other variables remain unchanged. In this research, service quality scale is built on many

items and in the end, three main items used are related to in-store employees, including

“Service employees at this store have a good product knowledge”, “service employees at this

store are willing to help customers”, and “service employees at this store showed respect to

me”. It can be seen that employee behaviour towards consumers and their knowledge are the

important indicators for customer satisfaction. Therefore, it can be said that the behaviour of

in-store employees strongly affects customer satisfaction. Based on our qualitative research

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(data from the interviews), all respondents expressed the importance of staff behaviour to

them; if consumers are happy with everything but in-store staff fail to show respect or

support, consumers will choose not to shop at that store again if there are other available

alternatives. The service quality related to in-store employees’ knowledge and attitudes

toward consumers is endorsed as one of the main drivers of customer satisfaction which is

placed third among factors influencing customer satisfaction. It contradicts the finding of

Gallarza and Saura (2006) where they did not find that service quality is an antecedent of

satisfaction in a travel-related context.

According to the statistical test results, H14 was supported - store image is positively

associated with customer satisfaction (0.188). This finding is consistent with previous studies

where Bouzaabia et al. (2013), Poncin and Mimoun (2014), Carpenter and Moore, (2009),

Shobeiri et al. (2013), Sivadas and Jindal (2017) found a strong association between store

image and satisfaction. It is an important driver of customer satisfaction (Du Preez et al.,

2008a) as it “provides value-added benefits to the shopper” (Saraswat et al. (2010:169). It

reflects the set of beliefs about stores’ relative attractiveness which are perceived by

consumers. In the list of 11 main factors affecting customer satisfaction, store image has

been placed fourth. The store image construct is built by three reliable items and proved its

validity via CFA: “The supermarket offers high-quality merchandise”, “All brands you

planned to buy were available”, and “Physical facilities are visually appealing”. These factors

in store image strongly contribute to the creation of customer satisfaction. In other words,

higher achieved customer sastifaction can be traced back to higher perceived store image.

However, the research of Andaleeb and Conway (2016) revealed a partly contradictory result

of store image relating to atmospherics not having a significant impact on customer

satisfaction.

That H6 was supported means that customer experience has a positive effect on customer

satisfaction (0.148). It means that if other measured constructs remain unchanged, customer

experience can explain 14.8 percent of variation in customer satisfaction. This finding is

consistent with the studies of Lin and Bennet (2014) and Terblanche (2018), who found that

customer experience is positively related to overall satisfaction. In this thesis, customer

experience has been measured by the following three reliable and validated items: “The

shopping experience is refreshing”, “The store has a welcoming atmosphere and the

temperature inside the store is comfortable”, and “The shopping experience made me relaxed

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and comfortable”. These factors could lead to higher customer satisfaction. In other words,

the result from this research indicates that good consumer experience will lead to higher

customer satisfaction.

According to the statistical test results, H21B was supported - good product quality is

positively associated with customer satisfaction (0.144). As explained in the literature review,

all judgments about product quality based on customers’ views and mindsets are regarded as

subjective and there has been limited research on how product quality directly influences

customer satisfaction. Most research has focused on the relationship between product

attributes and customer satisfaction, Wang et al. (2018) found there are strong linkages

between products’ attributes and customer satisfaction. The results of this research are

consistent and indirectly endorse the study of Wang et al. (2018) and El-Adly’s research

(2018) that the higher offered product quality will lead to higher levels of customer

satisfaction and product quality is confirmed as one of the main indicators of customer

satisfaction as consumers often expect to buy a product with good quality.

That H10A, H9B was supported means that high-perceived alternative attractiveness has

a negative influence on customer satisfaction (beta value is -0.113), switching costs have a

positive effect on customer satisfaction (beta value is 0.071). It means that when more

competitors are available, consumers tend not to remain satisfied with their current

supermarket. They might always be looking for a chance to switch if other benefits are

available. In that, alternative attractiveness can negatively explain 11.3 percent of variation in

satisfied behaviour, and if switching costs are high, consumers seem to be more satisfied with

their current grocery retailers because they might be afraid of changing to new retailers with

much effort in cost and time.

According to the results, H20B was statistically supported - good price offered positively

affects customer satisfaction (0.051). The relationship between price and customer

satisfaction is complicated. “Customers with lower incomes might have wished the product

could be cheaper, so their satisfaction decreased with the increase in price” (Wang et al.,

2018:4). Those who usually buy moderately-priced products might have a higher income

compared to the above group medium priced items relatively correlates to their quality. In

this case, the higher priced products would enhance customer satisfaction (Wang et al.,

2018). Eid (2015), Eid and El-Gohary (2015), El-Adly’s research (2018) shows that price has

a significant direct positive effect on customer satisfaction (0.140). It does not mean that

262

when price increases, consumers will be more satisfied. Based on the measured items of a

“Price” constructs, the above result means that consumers will be more satisfied if products

are offered at a reasonable price. The level of price influence on customer satisfaction in this

study was found to have much lower effects compared to other main indicators presented

above; not only that, Kim et al. (2016) could not find a relationship between price of

smartphones and customer satisfaction.

Besides that, in this research, H1B was supported; income has a positive effect on

customer satisfaction with beta value of 0.025. In that, if income increases, the level of

customer satisfaction slightly increases. And H2B was also supported; the location where

people stay has an effect on customer satisfaction (0.020). In this research, “1” was coded for

“Ha Noi”, “2” was Da Nang, “3” was “Ho Chi Minh”, “4” was “Binh Duong”, and “5” was

“Can Tho”. The positive relationship between location and customer satisfaction shows that

supermarket consumers in Ho Chi Minh, Binh Duong and Can Tho tend to be more satisfied

with their current supermarkets than that of Ha Noi and Da Nang. The reason could be that

the consumption style in the south is more generous than that of the north, and consumers

easily adapt and accept mistakes or changes.

Retail brand experience was found to have no direct relationship with customer

satisfaction (H11A). This finding is inconsistent with previous findings such as Kim et al.

(2015), Ha and Perks (2005), Khan and Rahman (2015), Ishida and Taylor (2012), where

they verified that retail brand experience directly influences customer satisfaction. There are

two main measured items of this construct, including “When I think of excellence, I think of

this retail brand name”, “I feel good of this retail brand because of their simple and better

structured bills”. Based on the statistical results, retail brand experience could not prove a

direct and positive relationship with customer satisfaction. However, in this study, retail

brand experience was found to be the most important indicator for customer loyalty

(presented at section 7.2.3).

H3B, H4B and H5B (age ranges affect customer satisfaction, gender affects customer

satisfaction, people who choose different supermarkets for shopping have different behaviour

on customer satisfaction respectively) were not supported. It means that age ranges, gender,

strategic groups do not show any impact on customer satisfaction.

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7.2.3. Results from all hypotheses related to customer loyalty (CL)

There are 7 main indicators for customer loyalty in the retailing industry, which are, in

descending order: retail brand experience, service quality related to in-store employees’

knowledge and attitudes toward consumers, customer satisfaction, promotion effects,

switching costs, e-service quality related to E-S-QUAL scale and alternative attractiveness. In

this finding, switching barriers showed a strong relationship with customer loyalty. Besides

that, price, store accessibility and habit also have a weak impact on customer loyalty. There is

a negative relationship between store accessibility and customer loyalty found. This is an

unexpected result. However, that consumers find it easy to access a supermarket does not

guarantee that they will be loyal to that supermarket; in this research, the easier access to

supermarkets, the lower the level of loyalty as a result because of consumers having a variety

of choices (high alternative attractiveness) and other benefits from other competitors (better

service quality, better brand name positioning and better promotion activities etc.). Higher

income consumers were found to be more loyal than lower income consumers in general.

Loyalty programmes were found as having a negative relationship with customer loyalty due

to programmes frustrating consumers to some extent. Customer perceived value, product

quality and corporate social responsibility were found to have no direct impact on customer

loyalty. Qualitative variables including age, gender, location of consumers and which

supermarkets they choose to frequent was found to have no influence on customer loyalty as

well.

The following part will demonstrate and investigate all constructs having a direct effect

on customer loyalty in detail. Based on the statistical results, factors having the most

important impact on customer loyalty will be presented first.

264

Dependent


CL

H11B 1 RBEX 0.306

H12C 2 SQ 0.179

H8 3 CS 0.178

H19B 4 PROE 0.141

H9C 5 SWC 0.113

H17D 6 ESQX2 0.106

H10B 7 ALA -0.101

H20C 8 PRICE 0.069

H26 9 HABIT 0.057

H1C 10 INCOME 0.024

H7B

CPV

Not

supported

H22B CSR

H21C PROQ

H5C Q4

H2C LOCATION

H3C AGE

H4C GENDER

H17C ESQX1

H15 STAC

H18 LPRO

Table 7.3: Factors directly affecting customer loyalty

According to the statistical test results, H11B was supported, customer loyalty is

positively affected by retail brand experience (0.306). This finding is consistent with previous

studies where Khan and Rahman (2015:66), Ishida and Taylor (2012) verified that “retail

brand experience influences brand loyalty”. In this research, retail brand experience was

found to be the most important factor affecting customer loyalty and it can explain 30.6

percent of variation in consumer loyal behaviour. In SEM model, “retail brand experience”

construct is built based on two main reliable items which have been validated at CFA,

including “When I think of excellence, I think of this retail brand name”, “I feel good with

this brand name because of their simple and better structured bills”. It is endorsed that when

supermarkets can create good brand names in consumers’ minds and also generate a good

brand experience, consumers will be more loyal to them; consumers are more likely to pay

more for the brand that they are committed to because they perceive many values that other

providers could not fulfill or imitate.

That H12C was supported means that the higher service quality offered leads to higher

levels of customer loyalty (0.179). The finding is consistent with previous studies, such as

Gallarza and Saura (2006); Eid (2015); Bolton and Drew (1991); Sivadas and Baker-Prewitt

(2000); Siu and Cheung (2001); Cronin et al. (2000); Athanassopoulos (2000), they also

found that service quality has a strong positive effect on loyalty. In this context, service

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quality was built based on three main items related to in-store employees’ knowledge and

attitudes toward consumers and service quality was found having a significant direct positive

impact on customer loyalty. If other variables remain unchanged, service quality can directly

explain 17.9 percent of variation in customer loyalty. The qualitative research shows that 100

percent of consumers interviewed endorsed that they might not be loyal to supermarkets

where service staff do not show respect or support to them even if other factors match with

their demands. However, the research of Chang and Yeh (2017) shows that there is no direct

relationship between service quality and customer loyalty, service quality affects customer

loyalty via a mediation of customer satisfaction.

According to the statistical test results, H8 was supported, customer satisfaction is

directly and positively associated with customer loyalty (0.178). This finding is consistent

with many previous studies where Perez and Bosque (2015), Rahman et al. (2016), Carpenter

(2008), Chen (2012), Bouzaabia et al. (2013), Kim et al. (2004), Babin et al. (2005), El-Adly

and Eid (2016), Liu et al. (2011), Lin and Bennett (2014), Han and Hyun (2012), Chang and

Yeh (2017), Kitapci et al. (2013), Han et al. (2011b) and Lee et al. (2007), Wong and Sohal

(2003), Calvo-Porral and Levy-Mangin (2015). They found that there are positively strong

relationships between customer satisfaction and customer loyalty. Chang and Wang

(2011:346) also concluded that “customer satisfaction has a significant impact on customer

loyalty (β=0.84m t-value= 4.81)”. However, in this research, the relationship between

customer satisfaction and customer loyalty has not proved as strong as expected, if all other

investigated variables remain unchanged, customer satisfaction can explain 17.8 percent of

variation in customer loyalty. This finding is consistent with some studies where researchers

have suggested that other groups of researchers have exaggerated the strength of the

relationship between customer satisfaction and loyalty. Miranda et al. (2005), Baumann et al.

(2012), Mutum et al. (2014), Cronin and Taylor (1992), Oliva et al. (1992), Mittal and Lassar

(1998) presented that there is evidence that satisfaction and loyalty are not always strongly

correlated. Mutum et al. (2014:947), suggests satisfaction might not be the best predictor of

customer loyalty and “the presence (or lack) of switching barriers may be the reason why

customers stay with (or leave) a firm”. Kumar et al. (2013:246) also concluded “the variance

explained by just satisfaction is rather small - around 8 percent”. In constrast, Liu et al (2015)

found that customer satisfaction itself is not an indicator for customer loyalty as they found

no relationship between customer satisfaction and customer loyalty. It can be noted that

satisfied consumers can be either loyal or not loyal to supermarkets, it might depend on

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switching barriers, higher alternative attractiveness, and lower switching costs might lead

satisfied consumers to switch to other providers and lower perceived alternative

attractiveness and higher switching costs might keep satisfied consumers loyal to their current

supermakets. However, unsatisfied consumers might have no loyalty if they have an

opportunity to switch. In the list of 7 main factors constituting customer loyalty, customer

satisfaction is placed third, after retail brand experience and service quality.

That H19B was supported means that promotion has a positive effect on customer

loyalty (0.141). This finding is consistent with previous studies which investigated the link

between sales promotion efforts and customer loyalty. Tung et al. (2011), Thaler (1985),

Zeithaml (1988), Grewal et al. (1998) found that promotion effects have a significant positive

impact on loyalty (see Figure 2.4.13). Kim (2017) found that “the experience of the previous

promotion in the initial stage could influence retention decisions substatially later”. In this

study, in the list of 12 main factors affecting customer loyalty in the retailing industry,

promotion effects are fourth with a relatively high loading of 0.141 compared to how

customer satisfaction affecting customer loyalty (0.178). The “promotion effects” construct

was built on three reliable scales and proved its validity via CFA, including “I find the

promotional activities of this supermarket to be very persuasive and positive”, “My

purchasing willingness arises from the promotional activities”, and “It is well worth going

shopping during the period of a sales promotion”. That promotion effects have a significant

positive relationship with customer loyalty can inform retailers that appealing promotion

activities are not only one of the main drivers for higher customer perceived value but also

one of the main indicators for customer loyalty as well. In this context, efficient promotion

effects can contribute 14.1 percent of variation in customer loyalty.

According to the statistical test results, H9C was supported, high-perceived switching

costs have a positive influence on customer loyalty (0.113) and H11B was also supported,

high-perceived alternative attractiveness has a negative influence on customer loyalty (-

0.101). These findings are consistent with previous research (Anderson and Narus, 1990;

Colgate and Norris, 2001; Mutum et al., 2014, Kim et al., 2018) where they found that when

the perception of alternative attractiveness is low, customers have a tendency towards

retention and more loyalty due to low perceived benefits of switching providers. Hirschman

(1970); Jones et al. (2007), Liu et al. (2011) and Mutum et al., (2014) presented that when

switching barriers are high, the option to exit will be limited and customers might have a

267

tendency towards loyalty. Qui et al. (2015:92) also found that “in the industries characterised

by relatively low switching costs, customers are less likely loyal compared to service

industries with relatively high switching costs”. Tung et al. (2011:32) found that “higher

perceived switching costs and lower attractiveness of competing alternatives are associated

with higher repurchase intentions”. However, they could not find a link between alternative

attractiveness and loyalty (p value is higher than 0.05). In this thesis, the relationship between

switching cost and customer loyalty is positive, higher switching costs lead consumers to be

more loyal to retailers and its loading is relatively high (0.113) as it explains 11.3 percent of

loyal behaviour compared to that of 40% found by Koutsothanassi et al. (2017) and the

finding from Ningsih and Segoro (2014:1018) that “if the variables of switching cost

increased for one unit, the customer loyalty would increase for 0.241 points, assuming that

other independent variable value was fixed”. Besides that, alternative attractiveness

negatively affects customer loyalty, if there are more options, many competitors are

available, and consumers tend not to be loyal to retailers. In other words, if alternative

competitors are highly available, consumers’ loyal behaviour toward their current retailers is

decreasing by 10.1 percent. These findings are slightly different with the study of Burnham et

al. (2003) where they found that switching costs have the lowest influence on customer

loyalty and the findings from Tung et al. (2011:35) which showed that “the relationship

between the attractiveness of alternative and loyalty is not significant” (see Figure 2.4.13)

and Kim et al. (2004) who found the impact of switching barriers on customer loyalty, but not

much compared to the customer satisfaction dimension. In conclusion, in this study,

switching barriers including switching costs and alternative attractiveness are considered as

one of the main factors affecting customer loyalty.

H17D was supported, (E-service quality about a core e-service quality scale (E-S-

QUAL)) has a significant positive effect on customer loyalty (0.106) while H17C (E-service

quality about website quality scale (W-S-QUAL)) has a significant positive effect on

customer loyalty was statistically significant, but not supported. The result showed that a

website quality scale has a negative impact on customer loyalty (-0.076). This is an

unexpected result: with a low loading website, consumers still remain loyal to supermarkets.

This result can be explained as follows: because the study did not separate e-loyal consumers

and offline loyal consumers, W-S-QUAL could not explain the whole customer loyalty

behaviour. Besides that, as noted and proved in H17D, E-S-QUAL related to reliability,

fulfillment, efficiency and privacy/security, the higher e-service quality about theseterms will

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lead to higher customer loyalty behaviour. E-S-QUAL can explain 10.9 percent of the

variation in customer loyalty in general. In a retailing context, e-service quality (E-S-QUAL)

is considered one of the main drivers of customer loyalty. Based on the statistical results,

customer loyalty increases even as E-S-QUAL decreases. It contradicts the theory that high e-

service quality relating to a website leads to higher customer loyalty. In this case, low e-

service quality relating to awebsite in parallel with high e-service quality related to E-S-

QUAL is still possible, creating a higher level of loyalty. The finding is partially consistent

with Yun and Good’s study (2007) where they confirmed that e-service can improve

customer loyalty. Ribbink et al. (2004:446) found “the e-service quality dimension of

assurance, i.e. trusting the merchant, influences loyalty via e-trust and e-satisfaction”. And

the study from Chang and Wang (2011:346) showed that e-service quality did not directly

significantly affect customer loyalty, but “it does so indirectly through the mediation of

perceived value and satisfaction”. However, in this research, e-service quality related to E-S-

QUAL was found to have a significant direct impact on customer loyalty.

In this research, H20C was supported - good price offered positively affects customer

loyalty (0.069). The positive direct relationship was found. This finding is consistent with

previous studies where Eid (2015), Eid and El-Gohary (2015), El-Adly’s research (2018)

shows that price has a direct positive effect on customer loyalty (0.088 with p-value <0.05).

In this study, a realistic price paid can explain 6.9 percent of variation in consumers’ loyal

behaviour. Compared to other indicators, price shows a weak effect on customer loyalty.

According to the statistical test results, H26 (Habit positively affects customer loyalty)

was supported. In this study, the “habit” construct was built on three reliable and validated

items: “I have been doing for a long time (shopping at this supermarket)”, “I have no need to

think about doing (shopping at this supermarket),”, “I do without thinking (getting used to

knowing the products I need are, and in many convenient ways)”. However, the effect of

habit on customer loyalty is weak with a beta value of 0.057. This suggests that a habitual

behaviour relatively contributes to customer loyalty to some extent. The study of Liu et al.

(2015) was consistent with this research finding where they also found the positively direct

linkage between customer loyalty and habit. However, in their studies, habit is a strong

determinant of loyalty (beta value is 0.39). This can be explained as follows. Although it can

not deny the role of habit in shopping, consumers are likely to choose where they often shop

and be loyal to that place if alternative choice is limited. However, based on the results from

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supermarket consumer interviews, the level of habit influencing customer loyalty is different

across age ranges and locations where consumers stay. For instance, older consumers are

afraid to change to a new store or a new brand name because they claim that they will be not

familiar with where products are located at their new choice while young consumers are

happy to try to shop at new places. Consumers who stay in an urban area where supermarkets

are located near their houses or childrens’ schools will choose to shop and be loyal to

supermarkets surrounding these areas or those who do not have much time to shop might

continue to shop at their current supermarkets, otherwise they will shop anywhere they want

if there are no constraints. These reasons can lead to different statistical results between

studies. This study can endorse that habit positively affects customer loyalty but the impact is

relatively weak.

That H1C was supported means that income has a positive effect on customer loyalty. In

this study, income shows it has a weak positive direct impact on customer loyalty with

loading of 0.024. It reveals that consumers with higher incomes, might have slightly higher

levels of loyalty than those who have lower incomes. There has been no previous research on

how income affects consumer loyalty.

H7B (Customer perceived value has a direct positive impact on customer loyalty) was

not supported. This can be explained as follows. Due to the existence of other constraints,

such as time limitation, inconvenient locations, prices, and different interests between

members of a family, consumers might perceive high value from a specific supermarket but it

does not mean that they are definitely loyal to that supermarket. The finding of this research

is inconsistent with the studies of Ishaq (2012), Cronin et al. (2000), Chen and Chen (2010),

Ryu e al. (2012), Choi et al. (2004), Pura (2005), El-Manstrly (2016), they found that

customer perceived values are positively and directly related to customer loyalty, Rasheed

and Abadi (2014:303) stated that “46.5 percent of variation in customer loyalty can be

described by perceived value”. However, Bei and Chiao (2001), El-Adly and Eid (2016)

found only an indirect relationship existing between these two variables. In this research, as

explained above, customer perceived value was found only to have a direct impact on

customer satisfaction and its indirect relationship with customer loyalty is mediated by

customer satisfaction; no direct impact was found.

That H22B (Corporate social responsibility is directly and positively associated with

customer loyalty) was not supported means that there is no direct relationship between CSR

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and customer loyalty. This finding is consistent with some previous studies where Carrian

and Attalla’s studies (2001), Kaplan et al. (2014), Chang and Yeh (2017), Salmones et al.

(2005), Chang and Yeh (2017) also could not find a relationship. Chang and Yeh’s results

(2017) found that there is no direct effect between CSR and customer loyalty. The

relationship will exist when a mediator, corporate image, existed, (Chang and Yeh, 2017;

Gurlek et al., 2017). Therefore, corporate image could be tested as a mediator in the

relationship between CSR and customer loyalty. However, in this research, measured items

proposed for “corporate image” had been removed from the whole dataset due to its low

loading or cross-factor loading reasons. Therefore, the proposed mediating relationships

could not be tested. In contrast, Yusof et al. (2015) found CSR relating to customer centricity

have a direct positive effect on customer loyalty and other groups of researchers, such as

Perez et al. (2013), Mandhachitara and Poolthong (2011), Leaniz and Rodriguez (2015),

Ofluoglu and Atilgan (2014), Liu et al. (2014) found that there is a positive relationship

between CSR image and customer loyalty.

In this research, product quality was found to have no direct relationship with customer

loyalty (H21C). As presented previously, product quality is one of the main indicators of

customer satisfaction. That H2C, H3C, H4C, H5C (location where people stay has an effect

on customer loyalty, age range affects customer loyalty, gender affects customer loyalty,

People who choose different supermarkets for shopping have different behaviour on customer

loyalty) were not supported mean that locations, age ranges and gender, supermarkets’

choices do not show their impact on consumers’ loyalty behaviour.

H15, store accessibility positively affects customer loyalty, is statistically significant but

not supported. According to the statistical result, store accessibility has a slight negative

impact on customer loyalty. This is an unexpected result. However, in this case, it can be

explained as follows. If there is plenty of alternative attractiveness, other competitors are

located near focal retailers where consumers usually choose to shop, the level of loyalty in

this case could not be guaranteed and explained by store accessibility of a focal retailer.

Consumers tend to compare focal retailers and other competitors if competition level is high

and competitive advantages may erode (Seiders et al., 2005). Therefore, consumers have a

tendency to be less loyal to a focal retailer. The finding is inconsistent with Swoboda et al.

(2013) who found store accessibility of a focal retailer to have a positive impact on its store

loyalty and store accessibilty of competitors to have a negative influence on store loyalty

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towards the focal retailer. However, Swoboda et al. (2013:253) and Gounaris and

Stathakopoulos (2004) emphasised that “customers tend to be less loyal to a focal retailer

when the brand schemes of its competitors are more positive, perceptions of competitors may

affect store loyalty towards the focal retailer negatively if equally strong retailers are

competing with one another”. Therefore, in this result, the hypothesis of store accessibility

(of a focal retailer) having a positive effect on customer loyalty was not supported. And it can

be noted that the effect of location accessibility on store loyalty depends on the local

competitive context. Again, this finding partly endorsed the above statement of Swoboda et

al. (2013).

H18 (Loyalty programmes have a positive effect on customer loyalty (-0.041)) was

statistically significant but not supported. In this research, loyalty programmes were found to

have a negative relationship with customer loyalty. The finding is consistent with Lin and

Bennett (2014) and Stauss et al. (2005) who indicated that loyalty programmes can frustrate

their customers and decrease the level of customer retention to some extent. As presented at

the literature review part, Gustafsson et al. (2004), Lacey and Morgan (2008:9) stated “no

evidence is found in support of H2b for how membership in loyalty programmes increases

customers’ willingness to share information”, “no evidence for H4b is found to demonstrate

that loyalty programme membership positively impacts the relationship between committed

customers and their willingness to engage in word-of-mouth referrals” and “no evidence is

found in support of H5b that loyalty programme membership positively magnifies the

influence of the relationship between commitment and increased repatronage intentions”.

Stauss et al. (2005:231) explained “some operational problems in collecting promised

incentives for loyal behaviour and complicated operational procedures of a telecom

company’s customer club are perceived negatively by customers”. The finding from this

research can be explained as above. Loyalty programmes somehow frustrate their customers

if there are problems occurring during the rewarding process. In this research, loyalty

programmes construct is built based on the three reliable scales and proved its validity via

CFA; “collecting points is entertaining”, “When I redeem my points, I am good at myself”,

and “I belong to a community of people who share the same values”, retailers should

carefully consider how to use their loyalty programmes to stimulate shopping and retain their

valuable consumers rather than frustrating them and make them feel uncomfortable. The

finding is not compatible with Chen and Wang (2009), Walsh et al. (2008); Ho et al. (2009),

Noordhoff et al. (2004), Gustafsson et al. (2004), Bowen and McCan (2015), Roehm et al.

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(2002), Halberg (2004), Verhoef (2003), Lewis (2004), Bolton et al. (2000) where they found

a positively strong relationship between the loyalty programmes offered and customer

loyalty.

7.3. Multi-group comparisons’ discussion (Comparisons across groups for factors

related to customer loyalty)

This research used chi-square test to investigate between many groups, including

strategic groups (between different supermarket business models), income, gender, age range,

location, occupation and education level. The full statistical results were presented at section

6.6.3.4. Appendix 7.1, 7.2 and 7.3 systematically present the results from comparisions across

groups for factors related to customer loyalty, customer satisfaction and customer perceived

value respectively. However, based on the objectives of this research, only differences across

groups for factors related to customer loyalty will be fully discussed (see Appendix 7.1).

Regarding differences between strategic groups, e-service quality related to E-S-QUAL

has a strong and positive impact on customer loyalty at three groups, including the group of

multipurpose premium supermarkets 1 (Lotte mart), premium supermarket chains with

convenience stores (Vinmart), the group of multipurpose supermarkets 2 (Aeon) but e-service

quality related to E-S-QUAL was found to have no effect on customer loyalty among the

specialised daily consumer goods store (BigC or Co.opmart). The reason could be that

consumers from the group of specialised daily consumer goods prefer to come direct to

supermarkets and buy products, the rate of online shopping of this group would therefore be

lower than other supermarket groups and therefore e-service quality is a factor that does not

influence customer loyalty here. It can be seen that three other groups differently position

their target markets and consumers; the real situation showed that these three groups are

actively using e-stores for online grocery selling and participants who choose to shop at the

group of specilised daily consumer goods might not use their e-stores. Besides that,

consumers who choose to shop at the group of multipurpose premium supermarkets 1 (Lotte

mart) are more likely to have a relatively high income and good education levels that enables

them to shop online or groups of office workers who do not have much time for offline

shopping. In addition, promotion effects have positive relationship with customer loyalty at

the group of specialised daily consumer goods but at the group of multipurpose supermarkets

2 (Aeon), this relationship was not supported. It is noted that supermarkets at the group of

specialised daily consumer goods usually offer a reasonable price and discount in order to

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keep their target consumers and promotion is one of their tools to attract consumers.

However, in the group of multipurpose supermarkets 2, there are a variety of attached

products offered and services instead of just daily consumer goods. It means that promotion

in this group is not an indicator for customer loyalty.

At the group of multipurpose premium supermarkets 1, higher perceived alternative

attractiveness will lead to decreases in the level of consumer loyalty toward their current

supermarket, alternative attractiveness can negatively explain 22.8 percent variation in

customer loyalty, this figure at premium supermarket chains with convenience stores is 17.2

percent and at the group of specialised daily consumer goods is only just 0.6 percent. These

findings showed that consumers from the group of multipurpose premium supermarkets 1

will be less loyal to their supermarkets than other groups when they perceive high alternative

attractiveness. It can be noted that a majority of consumers from the group of multipurpose

premium supermarkets 1 and premium supermarket chains with convenience stores have a

medium and high income; they are concerned more about product quality and service quality,

and they might be willing to switch to other providers since they can, even if it costs them

more money and time to switch. Consumers from the group of specialised daily consumer

goods usually choose daily consumer goods with reasonable prices; in this case, the low

perceived alternative attractiveness could not be a main reason for them to stay loyal, and

their loyal behaviour might be down to other factors. Besides that, the research found that

price has a positive influence on customer loyalty at the group of multipurpose premium

supermarkets 1 but this relationship was not supported at premium supermarket chains with

convenience stores and at the group of specialised daily consumer goods, the effect was

relatively weak (6.1%). As presented above, consumers of premium supermarket chains with

convenience stores do not have much concern about price issues as consumers of this group

have a high income and are concerned more about hygiene issues, product origins, location

advantages, product quality, service quality and so forth; that price has a strong and positive

influence on customer loyalty at the group of multipurpose premium supermarkets 1 does not

mean that consumers in this group expect to buy products at low price, based on the

measurement scales of price constructs and in this case, reasonable price means that “goods

at this store offer value for money” (PRICE3 variable), in accordance with the results from

consumer interview, consumers explained that price is important when they shop at

supermarkets. However, in return, other factors such as good product quality, service and

relaxing shopping environment are also important. Balancing between what they got and

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what they sacrified is a result of consumer perceived value, higher perceived value consumers

of this group seem to be happy to pay more to get “good value” products. Therefore, price is

also one of the indicators of customer loyalty to some extent.

Retail brand experience was found to have a stronger impact on customer loyalty for the

group of specialised daily consumer goods, compared with the group of multipurpose

premium supermarkets 1. At the group of specialised daily consumer goods, retail brand

experience can explain 32.6 percent variation in customer loyalty, this figure for the group of

multipurpose premium supermarkets 1 is 21.9 percent. In this research, that retail brand

experience was found as the most important indicator of customer loyalty presents that

consumers are concerned more about retail brand name and their brand experience. The

difference between two above examined groups can be explained as follows: supermarkets of

the group of specialised daily consumer goods have been one of the first supermarkets

established in the Vietnamese grocery market; consumers remember their brand name with

images of “supermarkets for the family”. Therefore, the brands created have been deeply

ingrained in consumers’ memories. In addition, offering a variety of daily consumer goods

connected with family-focused culture with a reasonable price can lead to a higher loyal

behaviour among consumers.

Regarding gender, this research found that the positive relationship between promotion

and customer loyalty is stronger for males. It means that promotion effects lead to loyalty

behaviour is stronger for males; with males, promotion can explain 21.2 percent variation in

customer loyalty, while for females it is 11 percent. In Vietnam, a female is normallhy the

person in charge of grocery shopping. Their loyal behaviour can be explained by many

factors. Males are regarded as easy consumers in terms of shopping behaviour. The finding

above showed that males are more strongly iinfluenced by the level of promotion. For

instance, males are often in charge of shopping for household electrical appliances and

technical equipment or ‘quick’ grocery shopping at supermarkets, where promotions can be

linked with their behaviour.

Regarding income, at the low income group, service quality can explain 13.1 percent in

variation of customer loyalty, while that of the medium income group is 28.4 percent. The

medium income group considers that service quality is one of the main indicators of their

loyalty behaviour. Due to the higher income, the medium income group of consumers expect

to have a higher service quality, in the case of high perceived alternative attractiveness, they

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are more likely to switch to other providers if service quality is low. There are other factors,

such as price and promotion which are more important than service quality in explaining the

loyal behaviour of consumers from the low income group. Coincidentally, the research found

that the low income group considers price to be one of the main factors affecting their loyalty

behaviour but price has no effect on customer loyalty at medium income group. It can be

easily explained that low income consumers with limited budgets, price can be their most

considered factor.

Regarding location, in Ho Chi Minh, habit and e-service quality related to E-S-QUAL

have been considered as one of the main indicators of customer loyalty while in Hanoi, these

relationships were not supported. Differences between locations can be explained as follows:

different regions have different consumption styles and their perception of loyalty is

different, these differences can be traced back to different cultures across the country. In

addition, comparison with Ho Chi Minh, the level of retail brand experience influencing

customer loyalty is stronger in Hanoi (see Appendix 7.1 for full comparisons across groups).

It is noted that consumers in Hanoi have different spending lifestyles, formality is popular

and a brand name seems to be more important. Those who have a good retail brand name

tend to be more loyal in Hanoi; they are less likely to change to something new (such as

choosing a new supermarket to shop when they are happy with a current supermarket brand

name) and in general, consumers in Ho Chi Minh, with generous spending styles will find it

easier to change or try new things. These differences can partly explain why the level of retail

brand experience influence on customer loyalty is stronger in Hanoi. The research also found

that service quality is also one of main indicators of customer loyalty in Ho Chi Minh but in

Da Nang, service quality was found to have no direct impact on customer loyalty. This can be

explained that with a high level of alternative attractiveness in Ho Chi Minh, consumers will

find other better providers if the service quality of supermarkets is low and based on the

statistical results, there are five main factors affecting customer loyalty in Da Nang: retail

brand experience, customer satisfaction, alternative attractiveness, promotion and switching

costs with coefficients of 0.347, 0.257, -0.172, 0.138 and 0.128 respectively; how supportive

service employees are does not affect customer loyalty. Besides that, the results also show

that in Da Nang service quality is one of the main indicators of customer satisfaction which is

directly connected to customer loyalty. Consumers in Da Nang are satisfied because of high

service quality which indirectly leads to loyal behaviour. For other places such as Binh

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Duong and Can Tho, the researcher only found differences relating to customer satisfaction

across locations.

Regarding age ranges, customer satisfaction has a strong and positive impact on

customer loyalty among 18-22 year-olds, however, among 41-55 year-olds, customer

satisfaction was found to have no relationship with customer loyalty. In Vietnam, consumers

aged from 18 to 22 years old are more likely to have less money which leads to limited

spending budgets compared with 41-55 year-olds; when they are satisfied they tend to be

more loyal while the older group (41-55 year-olds) will normally having a higher shopping

budget, higher demand for products and better alternative choices as well as brand name

issues. Satisfaction in this case cannot guarantee for their loyal behaviour. In addition, higher

perceived switching costs will lead the group of 18-22 year-olds to stay loyal to their current

supermarkets while there is no linkage between switching costs and customer loyalty among

41-55 year old consumers. The reason could be that the group of 18-22 year-olds are afraid of

switching costs and have an easier shopping behaviour than another group when their

shopping budgets are limited. In contrast, among the 41-55 year-olds are not concerned about

switching costs and are willing to pay more or travel a longer distance to their favourite

supermarkets. They have a variety of choice, so satisfaction will not lead to loyalty. Their

loyal behaviour could be explained by other factors. Besides that, as explained above, in

Vietnam, a majority of consumers from the 18-22 year-old group have no income or low

income compared to other groups as they are still experiencing their education at universities

or colleges. Their shopping expenditure seems to be much lower than other groups. In

addition, between these two groups, the impact of promotion/price/service quality on

customer loyalty is much stronger among 41-55 year-olds. This group considers

promotion/service quality as factors contributing towards a good and enjoyable shopping

experience. They might be more loyal to supermarkets if good promotion programmes and

higher service quality were offered.

Between the 23-30 and 31-40 year-old groups, e-service quality related to E-S-QUAL

was found to only have a positive and strong relationship with customer loyalty with the

group of 23-30 year-old consumers and at this group, price slightly affects customer loyalty

while price has no influence on customer loyalty among the 31-40 year-olds. It can be noticed

that the group of 23-30 year-olds are mostly actively using online shopping, and older groups

of consumers might mostly choose to shop ‘offline’ at stores. These things explain why no

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relationship could be found between e-service-quality and customer loyalty among 31-40

year-olds. Price was found to have no relationship with customer loyalty among the older

consumer group as their loyal behaviour could be explained by other factors, such as product

quality, brand name preference, habit or service quality. In addition, in this research, the

relationship between service quality and customer loyalty is stronger for the group of 23-30

year old consumers, compared with the group of 18-22 year olds. Consumers aged from 23 to

30 might more likely choose to switch to other providers if low service quality is perceived.

Again, it can be endorsed that the impact of service quality on customer loyalty is stronger

for older groups as explained above.

The linkage between switching costs and customer loyalty is stronger for the group of

over 55 year-oldss, compared with the group of 23-30 year-olds. When switching costs are

highly perceived, the group of over 55 year old consumers tends to remain to be loyal to

supermarkets as they are afraid of change and investing time and money to find alternative

providers.

Regarding occupation, the results show that habit is one of the main indicators of

customer loyalty among office staff while no relationship between these two constructs was

found at the group of housewives. The reason could be that office staff usually do not have

sufficient time for shopping at supermarkets compared to housewives who always have

plenty of shopping time. A construct “habit” includes three variables related to saving time (1

variable) and how familiar consumers are with where products are located in stores (2

varibales). Therefore, habit strongly influences the loyal behaviour of office staff. Eventually,

the office staff will choose to shop at their normal shopping place and are averse to change

because of their limited shopping time and the convenience of supermarket locations will

facilitate their shopping while the housewives loyal behaviour can be affected by other

factors, such as retail brand experience, service quality, promotion, switching costs and price.

The statistical results also demonstrate that customer satisfaction does not affect customer

loyalty among housewives. In addition, between three groups (students, self employment and

office staff), the positive relationship between retail brand experience and customer loyalty is

strongest for the group of students, followed by office staff and retail brand experience can

only explain 15.2 percent of the variation in customer loyalty among the self employed. The

reason could be that self employed customers are more likely to be motivated by service

quality rather than the retail brand experience while students and office staffs will likely have

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a fixed route to and from their place of work or study, so they may be more likely to shop at

supermarket that they perceive provide good retail brand experience and a good location.

Regarding education levels, two main differences were found between three groups.

Among college/undergraduates, the relationship between customer satisfaction and customer

loyalty is much stronger, compared with the group of A levels consumers. Customer

satisfaction can positively describe 40.6 percent variation in customer loyalty among college

and undergraduate consumers while the figure for the group of A level consumers is 14.5

percent. In fact, among college/undergraduate consumers, customer satisfaction is considered

the most important indicator of customer loyalty while the top three factors deciding

customer loyalty of A level consumers are retail brand experience, service quality and

customer satisfaction. The reason could be that A-level consumers often stay with their

parents, so their shopping choices will depend on their parent’s decisions. In this case,

satisfaction might not guarantee loyal behaviour from A-level consumers. The group of

college/undergraduate consumers are more likely to have their own spending budgets and can

control their shopping decisions, so when they are satisfied with a supermarket, they will be

more loyal.

The results show that e-service quality related to W-S-QUAL (website quality scale) has

a positive impact on customer loyalty among college/undergraduate consumers but a negative

impact was found at the group among GCSE’s consumers. The reason could be that

consumers from the GCSE group are less likely to be in charge of supermarket shopping, the

results show that even when good website quality is provided, consumers of this group still

do not show loyalty to their supermarkets. In contrast, among consumers from the

college/undergraduate group who can use the internet for supermarket online shopping, the

provision of a good quality website can explain 12.8 percent of the variation in customer

loyalty.

The next chapter completes the thesis with conclusion, contributions, limitation and futur

research opportunities.

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Chapter 8: Conclusion

8.1. Introduction

The aim of this thesis is to investigate factors affecting customer loyalty of different

strategic groups in the Vietnamese supermarket sector. In order to achieve this main aim,

many interviews and tests were conducted and the results have been shown and discussed

from chapter 4 to chapter 7. This chapter is going to summarise the main findings by briefly

presenting conclusions relating to the research questions, followed by other main results

found and contributions to theory, methodology and practice. Then, limitations of the

research will be demonstrated as well as recommendations for future research.

8.2. Summary of main findings

8.2.1. Conclusions regarding the research questions

RQ1: What factors directly affect customer loyalty in the Vietnamese supermarket

sector and at which level?

The results show that there are seven main indicators for customer loyalty in the retailing

industry, in descending order: retail brand experience, service quality related to service

employees’ knowledge and attitudes toward consumers, customer satisfaction, promotion

effects, switching costs, e-service quality related to E-S-QUAL scale and alternative

attractiveness. Retail brand experience can positively describe 30.6 percent variation in

customer loyalty, service quality c17.9 percent and customer satisfaction 17.8 percent. The

figures of promotion effects, switching costs, e-service quality related to E-S-QUAL scale

and alternative attractiveness are 14.1%, 11.3%, 10.6% and 10.1% respectively. In the

research findings, six out of the seven factors show a strong positive relationship with

customer loyalty; the exception being alternative attractiveness. Thus, for example, when

consumers’ retail brand experience is high, their loyalty will be high; when service

employees show respect and supportive knowledge to consumers, consumers will be loyal to

firms. This research confirms that customer satisfaction has a positive impact on customer

loyalty, but the influence’s level is not as high as expected. Again, customer satisfaction can

explain 17.8 percent variation in customer loyalty. Promotion is considered to be one of the

main indicators of customer loyalty in the supermarket sector, being fourth in the list of main

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elements influencing customer loyalty. Effective promotions will lead to higher loyal

behaviour among consumers. Switching barriers were seen to have a strong relationship with

customer loyalty. When satisfied consumers perceive higher switching costs, they retain

loyalty with their current supermarket, while higher perceived alternative attractiveness leads

to a low level of loyalty. Besides that, price, habit and income also have a slight positive

impact on customer loyalty. Higher income consumers were found to be more loyal than

lower income consumers in general.

A negative relationship between store accessibility and customer loyalty was found. This

was an unexpected result. However, that consumers find it easy to access to supermarkets

does not guarantee that they will be loyal to supermarkets; in this research, the easier access

to supermarkets, the lower level of loyalty due to consumers having a variety of choices

(alternative attractiveness) leading to better benefits offered from other competitors. For

example: better service quality, better brand name positioning or better promotion activities.

Loyalty programmes were found to have a negative relationship with customer loyalty in this

research due to programmes often frustrating consumers to some extent. Customer perceived

value, product quality and corporate social responsibility were found to have no direct impact

on customer loyalty. The hypothesis that e-service quality related to W-S-QUAL scale has a

positive impact on customer loyalty was not supported. Furthermore, qualitative variables

including age range, gender and location where consumers stay and which supermarkets they

choose to frequent were found to have no influence on customer loyalty.


The finding from this research confirmed that satisfaction is considered as one of the

main indicators of customer loyalty (as presented above). However, the level of impact was

not as high as expected - customer satisfaction can describe only 17.8 percent variation in

customer loyalty.

RQ3: What factors directly affect customer perceived value and customer satisfaction

in the Vietnamese supermarket sector and at what level?


This research found factors directly affecting customer perceived value which will be

demonstrated as follows in decending order of importance: price, in-store logistics, trust,

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promotion effects, e-service quality related to E-S-QUAL, switching costs, service quality

and customer service (see Table 7.1). The majority of these factors have a positive impact on

customer perceived value, with the exception of switching costs. For example, the better the

price offered, the higher the perceived value for consumers, and effective in-store logistics

will lead to higher customer perceived value. However, higher perceived switching costs will

decrease customer perceived value.

Customer satisfaction

This research revealed seven main factors directly affecting customer satisfaction in the

Vietnamese supermarket sector, which in decreasing order of importance are: customer

perceived value, in-store logistics, service quality related to service employees’ knowledge

and attitudes toward consumers, store image, customer experience, product quality and

alternative attractiveness. In particular, the first six factors showed a strong and positive

relationship with customer satisfaction. Customer perceived value is considered the main

indicator of customer loyalty, it can explain 30.1 percent variation in customer loyalty, in-

store logistics also demonstrated its vital role with customer satisfaction: with 23.9 percent

variation in customer satisfaction; the figures for service quality, store image, customer

experience, and product quality are 21.4 %, 18.8%, 14.8% and 14.4% respectively. In order

to maintain or improve customer satisfaction, these top six factors should be comprehensively

considered. The research also presented that alternative attractiveness can negatively explain

11.3 percent variation in customer satisfaction. When customers perceive high alternative

attractiveness, their level of satisfaction might decrease, and they might choose to switch to

other retailers if necessary. Besides that, switching costs and price also have a slightly direct

impact on customer satisfaction. Considering qualitative variables, income and location

where consumers stay slightly affects satisfaction behaviour. The results show that people

with higher incomes seem to be more satisfied than the group of lowincome consumers,

consumers in Ho Chi Minh, Binh Duong and Can Tho are more satisfied compared to those

in Ha Noi and Da Nang. Besides that, in this research, retail brand experience was found to

have no relationship with customer satisfaction but it is a main indicator of customer loyalty

which was presented in RQ1 at section 8.2.1. In addition, age range, gender, and supermarket

business models do not influence the level of customer satisfaction.

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In order to answer this question, multi-group analysis was conducted between researched

supermarkets. As analysed in chapter 4, there are five main strategic groups in the

Vietnamese supermarket sector (see section 4.1.2 for strategic group mapping). The

researcher used AMOS version 24 to investigate all possible differences between

supermarket business models. The full analysis was presented in section 7.5 and brief results

can be summarised as follows.

E-service quality relating to E-S-QUAL has a strong and positive impact on customer

loyalty in three groups, including the group of multipurpose premium supermarkets 1 (Lotte

mart), premium supermarket chains with convenience stores (Vinmart), and the group of

multipurpose supermarkets 2 (Aeon) but e-service quality relating to E-S-QUAL was found

to have no effect on customer loyalty in the group of specialised daily consumer goods (BigC

or Coopmart). In addition, promotion effects have a positive relationship with customer

loyalty at the group of specialised daily consumer goods but this relationship was not

supported at the group of specialised daily consumer goods. Price has a positive influence on

customer loyalty at the group of multipurpose premium supermarkets 1 but this relationship

was not supported at premium supermarket chains with convenience stores and at the group

of specialised daily consumer goods, the effect was relatively small (6.1%). At the group of

multipurpose premium supermarkets 1, higher perceived alternative attractiveness will lead to

decreases in the level of consumer loyalty towards their current supermarket, alternative

attractiveness can negatively explain 22.8 percent variation in customer loyalty, this figure at

premium supermarket chains with convenience stores is 17.2 percent and at the group of

specialised daily consumer goods is only 0.6 percent. Retail brand experience was found to

have a stronger impact on customer loyalty for the group of specialised daily consumer

goods, compared to the group of multipurpose premium supermarkets 1 (see Appendix 7.1

for full comparison across strategic groups).

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industry based on income, gender, locations, age groups, occupation and

education levels?

Differences in relationships between many constructs in the final researched model were

presented and discussed in detail in section 6.6.3.4.2 (gender), 6.6.3.4.3 (income groups),

6.6.3.4.4 (locations), 6.6.3.4.5 (age ranges), 6.6.3.4.6 (ocupation) (see Appendix 7.1 for full

comparision across groups for factors related to customer loyalty). This section is going to

briefly sumarise the results.

Among the low income group, service quality can explain 13.1 percent variation in

customer loyalty, while that of the medium income group is 28.4 percent. The medium

income group considers that service quality is one of the main indicators of their loyalty

behaviour. The research found that the low income group considers price is one of the main

factors affecting their loyalty behaviour while price was found to have no effect on customer

loyalty among the medium income group.

Regarding gender, this research found that the positive relationship between promotion

and customer loyalty is stronger for males. It means that promotion effects lead to stronger

loyalty behaviour among males; promotion can explain 21.2 percent variation in customer

loyalty while for females it is 11 percent.

As for location, in Ho Chi Minh habit and e-service quality related to E-S-QUAL are

considered the main indicators of customer loyalty while in Hanoi, these relationships were

unsupported; service quality is also a main indicator of customer loyalty in Ho Chi Minh but

in Da Nang, service quality was found to have no impact on customer loyalty. In addition,

compared with Ho Chi Minh, the level of retail brand experience influencing customer

loyalty is stronger in Hanoi. In other places such as Binh Duong and Can Tho, the researcher

only found differences relating to customer satisfaction across locations.

In terms of age ranges, customer satisfaction has a strong and positive impact on

customer loyalty among 18-22 year-olds, however, among 41-55 year-old consumers,

customer satisfaction was found to have no relationship with customer loyalty. Higher

perceived switching costs will lead 18-22 year old consumers to stay loyal to their current

supermarket while there is no linkage between switching costs and customer loyalty among

41-45 year old consumers. Between these two groups, the impact of promotion/price/service

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quality on customer loyalty is much stronger for 41-55 year- old consumers. Between the 23-

30 and 31-40 year-old groups, e-service quality related to E-S-QUAL was found only to have

a positive strong relationship with customer loyalty with 23-30 year-olds and in this group,

price slightly affects customer loyalty while price has no influence on customer loyalty

among 31-40 year-old consumers. In addition, the relationship between service quality and

customer loyalty is stronger for 23-30 year-olds, compared with 18-22 year-olds; the linkage

between switching costs and customer loyalty is stronger among over 55 yearolds, compared

with 23-30 year-olds.

Regarding occupation, the results show that habit is one of the main indicators of

customer loyalty in the group of office staff while no relationship was found between these

two constructs among housewives. The statistical results also demonstrate that customer

satisfaction does not affect customer loyalty among housewives. In addition, between three

groups (students, self employmed and office staff), the positive relationship between retail

brand experience and customer loyalty is strongest for students, followed by office staff, and

retail brand experience can only explain 15.2 percent of variation in customer loyalty in the

self employed.

Regarding education levels, two main differences were found between three groups.

Among college/undergraduate consumers, the relationship between customer satisfaction and

customer loyalty is much stronger, compared with to the A level group. Customer satisfaction

can positively describe 40.6 percent variation in customer loyalty among college and

undergraduate consumers while that figure for the group of A level consumers is 14.5

percent. In fact, among college/undergraduate consumers, customer satisfaction is considered

the most important indicator of customer loyalty while the top three factors deciding

customer loyalty among A level consumers are retail brand experience, service quality and

customer satisfaction. The results also demonstrated that e-service quality related to W-S-

QUAL (website quality scale) has a positive impact on customer loyalty among

college/undergraduate consumers but a negative impact among GCSE consumers.

8.2.2. Other conclusions

Regarding how qualitative variables affect three dependent constructs (customer

perceived value, customer satisfaction and customer loyalty), supermarket business models

(strategic groups) were found to have an impact on customer perceived value, meaning that

285

consumers who choose to shop at thespecialised daily consumer goods group (Coopmart or

BigC), the group of Multipurpose premium supermarkets 1 (Lotte Mart) and Premium

supermarket chains with convenience stores (Vinmart) have a slightly higher perceived value

compared to that of the group of Multipurpose supermarkets 2 (Aeon) or other supermarkets.

Income and location have a slightly positive impact on the level of customer satisfaction,

meaning that if income increases, the level of customer satisfaction slightly increases and

supermarket consumers in Ho Chi Minh, Binh Duong and Can Tho tend to be more satisfied

with their current supermarket than those of Ha Noi and Da Nang. Income was also found to

have a slightly positive influence on customer loyalty, meaning that consumers with higher

income, might in general have a higher.

8.2.3. Contributions to theory, methodology and practice

8.2.3.1 Contribution to theory

This research has three main contributions to the theory. Firstly, as presented at 2.4.5

(literature review section) and the results’ discussion at 7.2.2, switching costs and alternative

attractiveness in this research were treated as independent variables in comparison to

customer satisfaction (dependent variables). This research argues that the relationship

between customer satisfaction and switching barriers (switching costs and alternative

attractiveness) can be mutual, that switching costs and increases in alternative attractiveness

can influence the level of satisfaction. The higher perceived attractiveness of other providers

might decrease satisfaction levels and if switching costs are highly perceived, customer

perceived value might decrease and consumers tend to remain satisfied with current

providers; in other words, dissatisfied consumers might feel trapped and forced to remain

with current providers in the case of higher perceived switching costs. In previous research,

some researchers found that alternative attractiveness and switching costs can be both

mediators and moderators in the relationship between customer satifaction and customer

loyalty, meaning that they investigated how customer satisfaction affects perceived switching

costs and perceived alternative attractiveness. In contrast, based on the above arguments and

statistical results in this research, in the future, researchers can also examine how perceived

switching costs and perceived alternative attractiveness influence the level of customer

satisfaction.

286

Secondly, it is demonstrated in the review section that all theories related to the

relationships between constructs has already existed but testing theories have generated many

contrasting results and this research provides a comprehensive research model relating to

customer loyalty, customer satisfaction and customer perceived value in that all possible

factors which might affect these three dependent constructs were proposed (figure 2.5.19 -

the proposed conceptual framework), particularly, in the Vietnamese supermarket sector,

figure 6.4 has been chosen as a final model related to the research topic. The proposed

conceptual framework (figure 2.5.19) can be employed to investigate relationships between

many related constructs in different contexts, such as in different industries or in other

developing countries or developed countries with mature life cycles in their supermarket

sector. Besides that, the research indicated many qualitative variables such as age ranges,

income, location, gender, and occupation could be regarded as control variables which might

affect relationships between constructs; in this case, multigroup analysis should be examined.

Thirdly, the research has extended existing theories by investing and introducing the

term “strategic groups” of supermarket business models in relationships between constructs

in the proposed research model. The research findings presented the idea that the

relationships between constructs are different across strategic groups. For instance,

“consumers from the group of multipurpose premium supermarkets are concerned more

about service quality and e-service quality while consumers from the group of specialised

daily consumer goods do not. There is a positive and strong relationship between service

quality and customer perceived value, between e-service quality related to E-S-QUAL and

customer loyalty among the group of multipurpose premium supermarkets while that

relationship was not foubnd amongthe group of specialised daily consumer goods; at the

group of multipurpose premium supermarkets, price was found to have a strong and positive

impact on customer loyalty, however, at the group of specialised daily consumer goods, price

has a low impact on customer loyalty, and it can explain only 6.1% variation in customer

loyalty. Promotion is one of the main indicators of customer loyalty at the group of

specialised daily consumer goods but no above impact was found in the group of

multipurpose supermarkets 2.” (see detail analysis in section 7.5).

8.2.3.2. Contribution to methodological level

This research used the mix method of using both qualtitative and quantitative research.

The reseach shows that this mix method is the best way to deal with research topics related to

287

“What factors affect X (dependent variables) and at which level?”. Because of the nature of

this research, mapping the strategic groups that investigated supermarkets belong to was

conducted through expert interview; then, using qualitative research first via consumer

interviewing allowed the researcher to amend questionnaires to include enquiries that were

not included in the original proposed questionnaire. In this research, after consumer

interviewing, two more constructs, “TRUST” and “HABIT” were added into questionnaires.

The contents of questionnaires were also re-checked by experts in order to guarantee their

content validity. These results can again emphasise the importance of mixed methods in this

area; as the research focusing on how these two new constructs related to customer perceived

value, customer loyalty has been limited, interviewing (a qualitative research) helps the

researcher fully explore whether there are any other factors which might influence customer

perceived value, customer satisfaction and customer loyalty in a specific context – the

supermarket sector in Vietnam in this case. This process is highly recommended in exploring

relationships between factors.

The next steps were using many statistical techniques in exploratory factor analysis to

investigate the reliability of constructs, convergent and discriminant validity. Then,

confirmatory factor analysis also allowed the researcher to test reliability, convergent and

discriminant validity to re-endorse a valid and reliable level of all researched constructs. The

final scales used for all constructs in this reseach can be employed in other research.

To date and to the author’s knowledge, this is the first research using multigroup analysis

techniques in SEM to comprehensively investigate differences every single relationship in the

whole research model. Multigroup analysis demonstrates its significant impact on marketing

research, without this test, differences between groups might not be able to be explored. In

this research, differences between age range, income, location, gender, occupation,

supermarket business models and consumers’ education levels were examined, and the results

indicated that there are significant differences between groups. In order to acheive these

results, the newest updated function of AMOS version 24 and a Plugin tool named

“Invariance” from Gaskin and Lim (2018) were utilised. These tools facilitated the conduct of

the research conducted. It can be noticed that the “Invariance” tool cannot be run with

previous versions of AMOS. In the future, all valuable Plugin functions of AMOS version

24are strongly recommended for use in order to quickly and comprehensively achieve

statistical results.

288

8.2.3.3. Contribution to practice

The research achieved the orginal objectives of investigating relationships between other

independent constructs and customer loyalty. In addition, the research also revealed the list of

factors directly influencing customer perceived value and customer satisfaction. Besides that,

multigroup analysis, including age ranges, income, location, gender, occupation, educational

levels and supermarket business models were investigated as well. These efforts have brought

many advantatges for both academia and practitioners. This section is going to demonstrate

how the research contributes to practice.

The whole final research model revealed relationships between constructs. Practitioners

can perceive a brief insight into the linkages between customer percieved value, customer

satisfaction and customer loyalty.

In a supermarket sector, the top 9 factors affecting customer perceived value are price,

in-store logistics, trust, promotion, e-service quality related to E-S-QUAL, switching costs,

service quality andcustomer service (Table 7.1 presented the influence level). Therefore, in

order to achieve higher perceived value from consumers, practitioners should offer a

reasonable price, effective in-store logistics, build trust, offer more appealing promotion

activities, improve e- service quality related to E-S-QUAL, customer service and service

quality (especially service-employees’ knowledge and how they treat consumers) should be

considered carefully.

In a supermarket sector, the top 9 factors affecting customer satisfaction arecustomer

perceived value, in-store logistics, service quality, store image, customer experience, product

quality, alternative attractiveness, switching costs and price (Table 7.2 presented the

influence level). Therefore, in order to achive higher satisfaction from consumers,

practitioners should consider how to improve their perceived value (the above presented

contents); at the same time, in-store logistics, service quality (how service employees treat

consumers), store image are also considered to be main indicators of customer satisfaction.

Many consumers informed that in-store logistics had created comfortable feelings while

shopping because they knew where products were located and other logistics activities

facilitate their shopping; satisfaction will be a result if efficient in-store logistics are provided.

Besides that, creating a decent shopping environment leads to good customer experience

contributing to customer satisfaction. Price also affects the level of satisfaction. This research

289

found that switching costs and alternative attractiveness have an impact on customer

satisfaction, but these are regarded as external factors. However, practitioners should be

aware of the influencing level of these two factors in order to know how to keep current

consumers satisfied and avoid switching to other providers.

In the supermarket sector, the top 9 factors affecting customer loyalty are retail brand

experience, service quality, customer satisfaction, promotion, switching costs, e-service

quality related to E-S-QUAL, alternative attractiveness, price and habit (Table 7.3 presented

the influence level). Therefore, in order to keep consumers loyal, practitioners should be

aware of the importance of brand experience and making efforts to build a good brand name

in consumers’ minds. Good service quality relating to employees’ specialised knowledge and

how they treat consumers are also vital to keeping consumers loyal. Therefore, training of

staff should be one of the top priorities. The level of satisfaction also positively relates to the

level of loyalty. This research indicates that satisfaction is not the only way to engender

consumer loyalty. Practitioners should consider offering more appealing promotional

activities, improving e-service-quality related to E-S-QUAL and offering reasonable prices.

Again, two external factors (switching costs and alternative attractiveness) should be

considered by practitioners in order to avoid and reduce the level of consumers’ switching to

other providers. Besides that, consumer habits have also proved to have a slight linkage with

consumer loyal behaviour.

Apart from the contributions to practice presented above, the research explored

multigroup analysis (section 7.5) which is also considered as a main contributon;

practitioners can gain insights into how different relationships bexist etween constructs across

location, gender, income, occupation, education levels and supermarket business models.

Based on this, at each supermarket location, practitioners might employ different business

strategies in order to ensure their consumers achieve higher perceived values, satisfaction and

loyalty. Besides that, with each supermarket model, practitioners know where to improve to

get a higher loyalty level from consumers.

Based on the above results and suggestions, retailers who are already present in a retail

sector should know which strategic groups they belong to, and in order to gain more market

share and improve their profits; enhancing customer loyalty should be considered as one of

top priorities in firms. In addition, understanding the model applied in different groups can be

beneficial to retailers to some extent, retailers can attract their potential consumers who are

290

currently loyal to different supermarkets by improving service quality, brand experience, in-

store logistics as well as which promotion activities should be applied. For those who

potentially enter the retail sector, in particular supermarkets – future investors; the findings

from this research demonstrate its significant influence which domestic and foreign investors

will notice which customer segmentations or which kind of business models they should

invest to, based on their own competitive advantages in order to succeed in the Vietnamese

supermarket sector.

8.3. Thesis limitations and Recommendations for future research

There are some limitations to this research which will be presented below, followed by

recommendations for future research.

Due to a huge number of constructs researched, during exploratory factor analysis,

“COIMA”-corporate image construct has been eliminated from the data set. In order to

explain this problem, it is believed that the scale created for COIMA with 3 variables might

have a weak correlation with other variables in the dataset or other strong variables loading

for other constructs which can partly explain “corporate image” constructs such as store

image, in-store logistics and corporate social responsibility. Therefore, other research should

re-build the scales for corporate image.

The next limitation is that only three dependent variables have been investigated,

including customer perceived value, customer satisfaction and customer loyalty; in the

original proposed framework some other factors were also to be treated as dependent

variables such as trust (<--satisfaction), corporate image (<-- corporate social responsibility),

trust (<--store image), service quality (<--CSR), switching costs (<--customer satisfaction)

and alternative attractiveness (<-- customer satisfaction). However, with the complicated

research framework, the research could not cover every single relationship proposed and

found by other researchers. In the future, researchers can investigate these relationships

depending on research objectives.

Based on the main objectives of this research, mediation and moderation effects between

some constructs have not been investigated. In future, researchers could explore whether

customer satisfaction mediates relationships between customer experience, customer

perceived value, alternative attractiveness, service quality and customer loyalty (as has been

proposed by some researchers), and whether customer perceived value mediates relationships

291

between in-store logistics, customer service, trust and customer satisfaction. In addition,

whether loyalty programme membership moderates the relationship between customer

experience and customer satisfaction; whether switching costs moderate the relationship

between customer satisfaction and customer loyalty; and whether alternative attractiveness

moderates the relationship between customer satisfaction and customer loyalty.

One of the initial objectives of this research was to investigate the shopping behaviour of

Vietnamese supermarket consumers. Therefore, at the section one of the research

questionnaire, there are 20 questions relating to shopping behaviour. However, due to word

limitations and the main objectives having been given a higher priority for investigation, this

research did not investigate shopping behaviour generally and briefly presented at Appendix

5.5. In the future, depending on research objectives, researchers should explore shopping

behaviour in order to fully explain later statistical results.

The data for this research was collected at five main locations in Vietnam, whih have

mainly contributed to total supermarket revenue. This means that the level of competitors in

these areas is relatively high; so consumers might perceive higher alternative attractiveness

and switching costs. Further research should also try to collect data in areas with lower

competition to compare against this research to examine whether differences exist and which

factors affect customer loyalty in areas of lower competition.

At multigroup analysis, the research could not investigate deeply every single difference

between two constructs across groups due to word limitations, and the main objectives of this

research are not to explore every single difference, only the main differences across strategic

groups and factors relating to customer loyalty. The research showed statistical results at

section 6.6.3.4 and briefly presented the findings but could not fully explain all findings at

section 7.5. In future, researchers could conduct research by examining other groups and

different relationships between constructs and customer satisfaction, customer perceived

value (see statistical results at Appendix 7.2 and Appendix 7.3) more deeply. Furthermore,

due to limited participants from high income groups, the researcher could not investigate how

different the relationships between constructs are between low and high income groups. In

future, other researchers could try to collect more data from consumers of a high income

group in order to investigate these relationships. Besides that, even with up-to-date statistical

tools, this thesis only explores the differences between two-groups through investigating the

chi-square test due to limitation of the current research tool; in future, if new multigroup

292

analysis tools exist which allow researchers investigate differences between more than 2

groups, it would be ideal for researchers to compare differences between more than two

groups.

Finally, the proposed research framework could be replicated in order to investigate

whether results are different across markets (developing and developed countries), industries

(an eletronic sector and a retail sector) and contexts (between multichannel/omnichanel

contexts and traditional ones). In addition, variations between the shopping behaviors of

different generations should also be considered important to investigate in the future.

293

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APPENDICES

Appendix 2.1 - All hypotheses proposed in this research

Direct effects

H1A: Income has a positive effect on customer perceived value

H1B: Income has a positive effect on customer satisfaction

H1C: Income has a positive effect on customer loyalty

H2A: Location where people stay has a positive effect on customer perceived value

H2B: Location where people stay has a positive effect on customer satisfaction

H2C: Location where people stay has a positive effect on customer loyalty

H3A: Age positively affects customer perceived value

H3B: Age positively affects customer satisfaction

H3C: Age positively affects customer loyalty

H4A Gender positively affects customer perceived value

H4B Gender positively affects customer satisfaction

H4C: Gender positively affects customer loyalty

H5A: People who choose different supermarkets for shopping have different customer

perceived value

H5B: People who choose different supermarkets for shopping have different behavior on

customer satisfaction

H5C: People who choose different supermarkets for shopping have different behavior on

customer loyalty

H6: Customer experience has a positive effect on customer satisfaction

H7A: Customer perceived value has a positive influence on customer satisfaction

H7B: Customer perceived value has a direct positive impact on customer loyalty

H8: Customer satisfaction is directly and positively associated with customer loyalty

H9A: Switching costs have a negative effect on customer perceived value

H9B: Switching costs have a positive effect on customer satisfaction

H9C: High-perceived switching costs have a positive influence on customer loyalty

H10A: High-perceived alternative attractiveness has a negative influence on customer

satisfaction

H10B: High-perceived alternative attractiveness has a negative influence on customer loyalty

H11A: Customer satisfaction is positively affected by retail brand experience

H11B: Customer loyalty is positively affected by retail brand experience

H12A: There is a positive relationship between service quality and customer perceived value

H12B: There is a positive relationship between service quality and customer satisfaction

H12C: Service quality positively affects customer loyalty.

H13A: In-store logistics have a strong and positive effect on customer perceived value

H13B: In-store logistics have a strong and positive effect on customer satisfaction

H14: Store image is positively associated with customer satisfaction

H15: Store accessibility positively affects customer loyalty

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H16: The higher customer service, the better customer perceived value

H17X1: E-service quality has a positive effect on customer perceived value

H17X2: E-service quality has a positive effect on customer loyalty

H18: Loyalty programs have a positive effect on customer loyalty

H19A: Promotion effects positively affect customer perceived value

H19B: Promotion has a positive effect on customer loyalty

H20A: Good price offered positively affects customer perceived value

H20B: Good price offered positively affects customer satisfaction

H20C: Good price offered positively affects customer loyalty

H21A: Good product quality is positively associated with customer perceived value

H21B: Good product quality is positively associated with customer satisfaction

H21C: Good product quality is positively associated with customer loyalty

H22A: Cooperate social responsibility is directly and positively associated with customer

perceived value

H22B: Cooperate social responsibility is directly and positively associated with customer

loyalty

H23: Corporate social responsibility positively affects corporate image

H24: Corporate image positively affects customer satisfaction

H25: Trust positively affects customer perceived value

H26: Habit positively affects customer loyalty

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Appendix 2.2 - Linkage between hypotheses and research questions

Research questions Hypotheses


loyalty in the Vietnamese supermarket and at

which level?

Customer loyalty: H1C, H2C, H3C, H4C, H5C

H7B, H8, H9C, H10B, H12C, H15, H17C,

H17D, H18, H19B, H20C, H21C, H22B, H26

RQ2: Is customer satisfaction a major

indicator for customer loyalty or not?

H8


perceived value, customer satisfaction in the

Vietnamese supermarket and at which level?

Customer perceived value: H1A, H2A, H3A,

H4A, H5A, H9A, H12A, H13A, H16, H17A,

H17B, H19A, H20A, H21A, H22A, H25

Customer satisfaction: H1B, H2B, H3B, H4B,

H5B, H6, H7A, H9B, H10A, H12B, H13B, H14,

H20B, H21B, H24

RQ4: Are there any differences in terms of

factors affecting customer loyalty between

strategic groups in the Vietnamese retail

industry?

Multigroup analysis

RQ5: Are there differences between the

factors affecting customer loyalty in the retail

industry based on income, gender, location,

age groups, occupation and education levels?

Multigroup analysis

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Appendix 2.3 - Latent factors and manifest varibles used in this research

Manifest variables Sources

Customer

perceived value

CPV1 Products are valuable

Chang and Wang (2011) CPV2 Prices are fair

CPV3 Products are worthwhile

CPV4 Compared to the price we pay, we get reasonable quality

Eggert and Helm (2000) CPV5 Compared to the quality we get, we pay a reasonable price

CPV6 The purchasing relationship delivers us superior net-value.

Customer

satisfaction

CS1 Complete service offered by a supermarket is significantly above expected

Kitapci (2013) CS2 In general, my satisfaction level related to the supermarket that I have already dealt with is high

CS3 Assuming you view your entire experience with the supermarket, overall you are very satisfied with

the supermarket

CS4 Shopping at the supermarket has been an enjoyable experience Lin (2014), El-Adly (2016)

CS5 I am disappointed to have been in this store Bouzaabia (2013)

Customer loyalty

CL1 In the near future, I am sure to repurchase at this supermarket and buy more at this one than at

another retailer Swoboda (2013)

CL2 I am willing to pay more as compared to other retailers for the products I buy from this retailer Srivastava (2016)

CL3 I will say positive things about the retailers and recommend it to others Srivastava (2016), El-Adly (2016)

CL4 I would consider the supermarket my first choice to do shopping Lin (2014), Terblanche (2018)

CL5 I will always continue to choose the products of this grocery store instead others Oliver (1997)

In-store logistics

ISL1 In the supermarket, the shelves are well-stocked

Bouzaabia (2013)

ÍSL2 No problems when returning merchandise

ISL3 In the supermarket, there are enough shopping carts

ISL4 In this supermarket, sufficient carrier bags are provided by the cashiers

ISL5 In this supermarkets, all products can be easily reached

ÍSL6 Prices on the product labels are correct

ISL7 The sell-by date is well indicated on the products

Service quality

SQ1 I would say that the quality of my interaction with the provider’s employees is high

Liu et al. (2011) SQ2 I always have an excellent experience when I interact with my service provider

SQ3 I feel good about what my service provider provides to its customers.

SQ4 Service employees at this store have good product knowledge Jiang et al. (2018) SQ5 Service employees at this store are willing to help customers

SQ6 Service employees at this store showed respect to me

E-service quality

ESQ1 Organisation compensates me when what I ordered does not arrive on time

Zemblyte (2015)

ESQ2 Organisation picks up items I want to return with minimum hassle

ESQ3 Organisation makes accurate services (accurate records of consumers, accurate account, etc..)

ESQ4 Organisation provides me with different options for payment, delivering and/or returning items

ESQ5 Organisation is truthful about its offerings, it has in stock the items it claims to have

ESQ6 Organisation offers a clear return policy and guarantee

ESQ7 Organisation’s site loads it pages fast and easy

ESQ8 Organisation’s site enables me to complete a transaction quickly

ESQ9 Organisation presents guarantee and privacy policy on its site

ESQ10 My order is quickly confirmed and kept by the organisation

Product quality

PROQ1 This store has a lot of variety

Jiang et al. (2018)

PROQ2 Products in this store are of consistent quality

PROQ3 Products available in this store are good workmanship

PROQ4 Products in this store are of good design

Price

PRICE1 Goods at this store are reasonably priced Jiang et al. (2018)

PRICE2 The prices of the products in this supermarket are cheaper than others Emi Moriuchi, 2016

PRICE3 Goods at this store offer value for money Jiang et al. (2018)

Customer service

CUSER1 Having a short waiting time at the checkouts

Kursunluoglu (2014)

CUSER2 Having clean restrooms

CUSER3 Doing faster transactions without waiting customers

CUSER4 Having easy product return policy

CUSER5 Always having an available slot in the car park

CUSER6 Broadcasting nice music inside the supermarket

CUSER7 Providing noiseless shopping possibility

CUSER8 Having informative in-store employees in encounter stage

333

CUSER9 Having a beautiful gift wrap

CUSER10 Doing demonstrations about how to use the product

Customer

experience

CUSEXP1 The shopping experience is refreshing

Srivastava (2016)

CUSEXP2 The store has a welcoming atmosphere and the temperature inside the store is comfortable

CUSEXP3 The shopping experience made me relaxed and comfortable

CUSEXP4 I did not feel deceived by the service staff (such as pricing, special deals, discounts, gifts etc)

Retail brand

experience

RBEXP1 When I think of excellence, I think of this retail brand name

Khan and Rahman (2016)

RBEXP2 I feel good with this retail brand because of their simple and better structured bills

RBEXP3 Point-of-sales contact produces a strong impression on my intellect

RBEXP4 Helping nature of salespersons at this retail brand name has built a better shopping experience

RBEXP5 I find events of this retail brand interesting in the sensory way

RBEXP6 Stories of this brand stimulate my curiosity

Store image

STIMA1 The supermarket offers high-quality merchandise

Bouzaabia (2013)

STIMA2 All brands you planned to buy were available

STIMA3 Physical facilities are visually appealing

STIMA4 It is easy to find products in promotion

STIMA5 Employees are well informed, courteous and supportive

STIMA6 The layout of this store is attractive Jiang et al. (2018)

STIMA7 The atmosphere in this store is pleasant

Corporate image

COIMA1 This company has a good image among consumers Calvo (2015) COIMA2 I have a good image about the company

COIMA3 This company has a good image compared to other competing companies

Corporate social

responsibility

CSR1 The supermarket concern with respecting and protecting the natural environment

Perez (2015)

CSR2 They contribute money to cultural and social events

CSR3 This supermarket treats its customer honestly

CSR4 This supermarket makes an effort to know customers’ needs.

CSR5 This supermarket offers safety at work to its employees

CSR6 This supermarket treats its employees fairly (without discrimination and abuses)

Trust

TRUST1 I trust this retailer

Lombart (2014) TRUST2 I consider that to shop in the stores of this retailer is a guarantee

TRUST3 I believe that this retailer is honest/sincere towards its consumers

TRUST4 This retailer regularly renews itself to meet the needs of its customers

Habit

HABIT1 I have been doing for a long time (shopping at this supermarket)

Olsen (2013) HABIT2 I have no need to think about doing (shopping at this supermarket)

HABIT3 I do without thinking (getting used to know where is the products I need, and in many convenient

ways)

Store accessibility

STAC1 I can get to store X quickly

Swoboda (2013) STAC2 I can get to store X without problems

STAC3 I can get to store easily

Alternative

attractiveness

ALA1 Probably, I would be satisfied with another company Calvo (2015)

ALA2 There are other good companies to choose from

ALA3 I need to change the place for shopping, there are other good department stores to choose from Tung (2011)

ALA4 I would be more satisfied with the products and services of other department stores

Switching costs

SWC1 Switching to other providers will bring economic loss Liu et al. (2011)

SWC2 Switching to other providers will bring psychological burden

SWC3 Search and evaluate the untested service department store costs you time and effort Tung (2011)

SWC4 An uncertainty feeling is relative to the untested service department store

SWC5 In general, it will be a hassle switching to another hotel Qui et al. (2015) SWC6 If I switch to a new brand name, I will miss some of the services and benefits by the loyalty program

from this brand name (mileage and membership service)

Loyalty programs

LPRO1 I shop at a lower financial cost (I save money)

Stathopoulou (2016)

LPRO2 Collecting points is entertaining

LPRO3 When I redeem my points, I am good at myself

LPRO4 I belong to a community of people who share the same values

LPRO5 They take better care of me

LPRO6 I feel I am more distinguished than other customers

Promotion effects

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Appendix 3.1 – Research Ethics approval letter

PROE1 I find the promotional activities of this online supermarket to be very persuasive and positive Emi Moriuchi (2016)

PROE2 My purchasing willingness arises from the promotional activities Tung (2011)

PROE3 It is well worth going shopping during the period of a sales promotion

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Appendix 3.2 - Guide used for expert’s semi-structured interviews

Expert’s semi-structured interviews

Factors affecting customer loyalty of different strategic groups in the Vietnamese

supermarket sector

I am a lecturer at the University of Economics and Finance Ho Chi Minh City, Vietnam and a

researcher at the University of Hull, United Kingdom. I am conducting a research study

investigating factors affecting customer loyalty of different strategic groups in the

Vietnamese supermarket sector.

I believe this research may interest you as an expert in strategy and hence invite you to

participate in this study. I would be grateful if you could spare between 60 and 75 minutes to

complete the interview below. If you would like to receive a copy of the aggregate results of

this interview, please provide your e-mail address at the end of the interview.

Participation in this study is voluntary. All information you provide is strictly confidential.

Your name and other details will not appear in the report resulting from this study. Only the

researchers associated with this project will have access to the data. There are no known or

anticipated risks to you as a participant in this study.

Should you have any concerns about the conduct of this research study, please contact me as

follows: Thi Diem Em Nguyen, Business School, University of Hull, Cottingham Road, Hull,

HU6 7RX; Tel No (+44) 7895890826/ (+84) 963694050; Email [email protected].

If you are content to participate in this research project, I would be grateful if you could sign

the following Statement.

By completing this interview, I consent and understand that

1. Answers to the interview questions will be coded and no names or other personal data

other than general demographic data will be collected, i.e. participants will be fully

anonymous to the researchers.

2. Aggregated results will be used for research purposes and may be reported in scientific and

academic journals, but no individual results, i.e. at respondent level, will be released.

3. I am free to withdraw consent at any time during the interview simply by abandoning the

interview in which case participation in the research study will immediately cease and any

information obtained to that point will not be used.

Signed: ____________________________________ Date: ____________

mailto:[email protected]

336

The current retail situation

Question 1: Can you give me a brief review of the current overall state of the Vietnamese

retail industry?

Question 2: Do you have any comments on the situation in the supermarket sector as well as

the competitive environment?

Strategic groups

Question 3: Normally, how can we group firms into their right strategic groups? Which

techniques can we use?

Question 4: Based on the Table 2.3.1 (shown during interview process), there are 12

supermarkets in Vietnam, how can we group them into different strategic groups and why?

Customer loyalty

Question 5: Based on your previous research and experience, which possible factors might

affect customer loyalty?

Question 6: Do you consider there is a linkage between customer perceived value, customer

satisfaction and customer loyalty?

337

Appendix 3.3 – Questionnaire used in supermarkets’ consumer interviewing

SEMI-STRUCTURED INTERVIEW GUIDE FOR SUPERMARKET CONSUMERS

I am a lecturer at the University of Economics and Finance Ho Chi Minh City, Vietnam and a




I believe this research may interest you as a supermarket consumer and hence invite you to

participate in this study. I would be grateful if you could take between 50 and 60 minutes to

complete the interview. If you would like to receive a copy of the aggregate results of this

interview, please provide your e-mail address at the end of the interview.










By completing this interview, I consent and understand that

1. Answers to the interview questions will be coded and no names or other personal data

(other than general demographic data) will be collected, i.e. participants will be fully

anonymous to the researchers.


academic journals, but no individual results, i.e. at participant level, will be released.

3. I am free to withdraw consent at any time during the interview completion by simply

abandoning the interview in which case participation in the research study will immediately

cease and any information obtained to that point will not be used.

Signed: ____________________________________ Date: ____________

Time of the interview:______to _________


338

1. Which supermarkets do you have in your city? Please name them.

2. How many times a week do you visit a supermarket?

3. Do you prefer shopping at supermarkets or traditional markets, and for what reasons?

4. As regards supermarkets, which is uppermost most in your mind, and why? Is this

always your top choice?

5. Can you tell me the main reason for preferring this supermarket?

6. Which factors influence your loyalty to the supermarket? Please list at least 5 factors

in descending order of preference?

7. What factors affect your satisfaction with the supermarket?

8. Please recount your past experiences, both good and bad about the quality of service

at this supermarket.

9. If you could switch to other supermarkets without incurring switching costs (such as

time, finance), would you be willing to switch?

10. If you are not satisfied with the service or the quality of the products at a supermarket,

will you continue to visit and shop there?

11. In your opinion, how does store image affect your perception of a supermarket

perceptions and your satisfaction with the shopping experience?

12. At which kinds of supermarkets do you wish to shop? Please describe.

13. Does corporate image affect your choice as to which supermarkets to use?

14. Does corporate social responsibility affect your choice as to which supermarkets to

frequent?

15. Do you think loyalty programmes such as bonus points, discounts and gifts will affect

your decision?

16. If other supermarkets offer appealing promotions or discounts, would you be ready to

switch to them?

17. If you are consistently loyal to a specific supermarket, would the opening of a rival

supermarket in a convenient location near to you cause you to consider switching to

the new supermarket (Suppose you are always loyal to specific supermarket A, if

supermarket B opens a store near you or easier for you to get there, do you wish to

switch to shop at supermarket B?)

18. Do you use online service at supermarkets (such as online ordering or home delivery

or product discussions)? What do you expect from supermarkets online service?

19. Do you consider your preferred supermarket meets your needs in respect of products

and services?

20. Do you think the prices at your preferred supermarket are reasonable?

21. With regard to customer service at this supermarket can you list what factors you are

satisfied and dissatisfied with?

22. When you shop at the supermarket, how do you feel? (For example are you relaxed,

are you respected, do you find the experience enjoyable?)

23. What are your views on the supermarket’s branding? Please tell me more about your

opinion of the importance of branding?

24. Please share with me your thoughts about the supermarket’s in-store logistic services?

(For example, are the shelves well-stocked, is it easy to make returns, can all products

339

be easily located and reached, are there sufficient shopping carts, are correct prices

displayed on the product labels?)

25. Are you loyal to that supermarket brand? Please rank from 1 to 5 (1 means “very

loyal”, 5 means “not very loyal”)

26. Are you satisfied with the service quality offered? On a scale of 1 to 5, how satisfied

are you (with 1 suggesting “very dissatisfied”, and 5 meaning “very satisfied”)? Did

staff respond enthusiastically and courteously when asked for asdsistance?

27. Regarding supermarkets generally, what criteria will you use to choose your

favourite?

28. Do you consider price to be the main factor choosing which supermarkets you should

use? If not, please explain.

29. Does a supermarket’s brand name affect your choice?

30. “I choose this supermarket’s brand name because it projects a good store image”. Do

you agree with this statement?

31. Suppose that there are two different supermarkets with which you feel satisfied, all

other factors being equal, with one supermarket being a domestic brand name, and the

other having a foreign brand name, which one will you choose, and hy?

32. In your family, who is responsible for buying grocery products? How many people

live in your house? Do you cook/eat separately or together?

33. Where do you usually go to buy daily food and groceries?

34. Are you loyal to a particular supermarket brand name or a specific store?

35. “In Vietnam, the majority of people who are responsible for buying foods and

grocery products are housewives, men do not usually deal with these matters”. Do

you agree with this statement?

Gender :

Age :

Location :

Thank you for your participation!

With kind regards,

Thi Diem Em Nguyen

340

Appendix 3.4 – Questionnaire survey

FACTORS AFFECTING CUSTOMER LOYALTY OF DIFFERENT GROUPS IN THE VIETNAMESE SUPERMARKET SECTOR

I am a lecturer at the University of Economics and Finance Ho Chi Minh city, Vietnam and a




I believe this research may interest you as a supermarket consumer and hence invite you to

participate in this study. I would be grateful if you could take between 15 and 20 minutes to

complete the survey below. If you would like to receive a copy of the aggregate results of

this survey research, please provide your e-mail address at the end of the survey.










By completing this survey I consent and understand that

1. Answers to the survey questions will be coded and no names or other personal data other

than general demographic data will be collected, i.e. participants will be fully anonymous to

the researchers.


academic journals, but no individual results, i.e. at respondent level, will be released.

3. I am free to withdraw consent at any time during completion of the survey simply by

abandoning the survey in which case participation in the research study will immediately

cease and any information obtained to that point will not be used.

Signed: ____________________________________ Date: ____________

Time of survey:______to _________


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Section 1: Supermarket shopping behaviour

1. Overall, where do you prefer to go for grocery shopping?

□ Supermarkets □ Traditional markets □ Other

2. How often do you go to traditional markets?

Once a day Twice a week Three times a week

Once a month Twice a month Other

3. How often do you go to supermarkets?

Once a day Twice a week Three times a week

Once a month Twice a month Other

4. Which supermarket do you usually go? (Please just choose one option)

Co.opmart or Big C

Lotte Mart

Vinmart

AEON

Other; please name __________

5. Do you have any loyalty cards from the supermarket which you have just chosen as your

answer to Question 4?

Yes No

6. For hHow long have you possessed the card?

I have no loyalty card

Less than 1 year

1-3 years

More than 3 years

7. Do you consider you are loyal to the supermarket chosen in question 4?

Yes No

From the following questions, when a supermarket is mentioned, please answer in respect

of the supermarket you normally use as noted in your answer to Question 4 above.

8. How satisfied are you with the supermarket? (1 meaning “very dissatisfied”, 5 meaning

“very satisfied”)

1 2 3 4 5

9. How satisfied are you with the service quality offeredby this supermarket? (where 1 means

“very dissatisfied”, and 5 means “very satisfied”)

1 2 3 4 5

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10. Do you think your favourite supermarkets meet your needs?

□ Yes □ No □ Partly met

11. If you are not satisfied with the service or the quality of the products at the supermarket, will

you continue to visit and shop there?

□ Yes □ No

12. Will you still stay with your favourite supermarket even if you see alternative attractiveness

offered by other supermarkets?

□ Yes □ No

13. “I choose this supermarket’s brand name because it projects a good store image”. Do you

agree with the above statement?

□ Yes □ No

14. Do you think loyalty programmes such as bonus points, discounts and gifts will affect your

decision?

□ Yes □ No

15. If other supermarkets offer appealing promotions or discounts, would you be willing to

switch to them?

□ Yes □ No

16. How many loyalty cards do you have for grocery shopping from different supermarkets?

0 1 2 3 More than 4

17. If you are consistently loyal to a specific supermarket would the opening of a rival

supermarket in a convenient location near to you cause you to consider switching to the new

supermarket?

□ Yes □ No

18. Does a supermarket’s brand name affect your choices?

□ Yes □ No

19. Suppose that there are two different supermarkets with which you feel satisfied, all other

factors being equal, with one supermarket being a domestic brand name, and the other

having a foreign brand name, which one will you choose?

Domestic brand name Foreign brand name

20. Are you responsible for buying grocery products for the whole family or for yourself?

The whole family Myself

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I am not in charge with buying grocery products

Section 2: Customers’ response

Note: The following questions should still be answered by reference to the

supermarket noted in your answer to Question 4, Part 1.

Please indicate your level of agreement towards the following statements using a scale from 1 to

5, where 1 means “strongly disagree” and 5 means “strongly agree”:

Statements 1 2 3 4 5


Products are valuable □ □ □ □ □

Prices are fair □ □ □ □ □

Products are worthwhile □ □ □ □ □

Compared to the price we pay, we get reasonable quality □ □ □ □ □

Compared to the quality we get, we pay a reasonable price □ □ □ □ □

The purchasing relationship delivers us superior net-value. □ □ □ □ □

Customer satisfaction

Complete service offered by a supermarket is significantly above expected □ □ □ □ □

In general, my satisfaction level relating to the supermarket that I deal with is high □ □ □ □ □

Assuming you view your entire experience with the supermarket, overall you are very satisfied with the supermarket

□ □ □ □ □

Shopping at the supermarket has been an enjoyable experience □ □ □ □ □

I am disappointed to have been in this store □ □ □ □ □

Customer loyalty

In the near future, I am sure to repurchase at this supermarket and buy more here than at another retailer

□ □ □ □ □

I am willing to pay more as compared to other retailers for the products I buy from this retailer □ □ □ □ □

I will say positive things about the retailer and recommend it to others □ □ □ □ □

I would consider the supermarket my first choice for shopping □ □ □ □ □

I will always continue to choose the products of this grocery storeahead of others □ □ □ □ □

Section 3: Perception of Quality

Note: as before, these questions should be answered by reference to the

supermarket named in your answer to Question 4, Part 1.




In-store logistics

In the supermarket, the shelves are well-stocked □ □ □ □ □

344

I have had no problems when returning merchandise □ □ □ □ □

In the supermarket, there aresufficient shopping carts □ □ □ □ □

In this supermarket, sufficient carrier bags are provided by the cashiers □ □ □ □ □

In this supermarket, all products can be easily located and reached □ □ □ □ □

Prices on product labels are correct □ □ □ □ □

The sell-by date is well indicated on the products □ □ □ □ □

Service quality

I would say that the quality of my interaction with the supermarket’s employees is high □ □ □ □ □

I always have an excellent experience when I interact with my service provider □ □ □ □ □

I feel good about what my service provider provides to its customers. □ □ □ □ □

Service employees at this store have good product knowledge □ □ □ □ □

Service employees at this store are willing to help customers □ □ □ □ □

Service employees at this store showed respect to me □ □ □ □ □

E-service quality

Organisation compensates me when what I ordered does not arrive on time □ □ □ □ □

Organisation picks up items I want to return with minimum hassle □ □ □ □ □

Organisation makes accurate services (accurate records of consumers, accurate account, etc..) □ □ □ □ □

Organisation provides me with different options for payment, delivering and/or returning items □ □ □ □ □

Organisation is truthful about its offerings, it has in stock the items it claims to have □ □ □ □ □

Organisation offers a clear return policy and guarantee □ □ □ □ □

Organisation’s site loads it pages fast and easy □ □ □ □ □

Organisation’s site enables me to complete a transaction quickly □ □ □ □ □

Organisation presents guarantee and privacy policy on its site □ □ □ □ □

My order is quickly confirmed and kept by the organisation □ □ □ □ □

Product quality

This store has a lot of variety □ □ □ □ □

Products in this store are of consistent quality □ □ □ □ □

Products available in this store display good workmanship □ □ □ □ □

Products in this store are of good design □ □ □ □ □

Price

Goods at this store are reasonably priced □ □ □ □ □

In general, product prices in this supermarket are cheaper than other supermarkets

Goods at this store offer value for money □ □ □ □ □

Section 4: Perception of Customer Service


supermarket named in your answer to Question 4, Part 1.



345


Customer service

The supermarket has a short waiting time at the checkouts □ □ □ □ □

Has clean restrooms □ □ □ □ □

Offers faster transactions without waiting customers □ □ □ □ □

Has an easy product return policy □ □ □ □ □

Always has available slots in the car park □ □ □ □ □

Broadcasts nice music □ □ □ □ □

Provides noiseless shoppin □ □ □ □ □

Has informative in-store employees in encounter stage □ □ □ □ □

Has a beautiful gift wrap □ □ □ □ □

Does demonstrations about how to use the product □ □ □ □ □

Customer experience

The shopping experience is refreshing □ □ □ □ □

The store has a welcoming atmosphere and the temperature inside the store is comfortable □ □ □ □ □

The shopping experience made me relaxed and comfortable □ □ □ □ □

I did not feel deceived by the service staff (such as on pricing, special deals, discounts, gifts etc) □ □ □ □ □

Retail brand experience

When I think of excellence, I think of this retail brand name □ □ □ □ □

I feel good with this retail brand because of their simple and better structured bills □ □ □ □ □

Points-of-sale contact produces a strong impression on my intellect □ □ □ □ □

The nature of salespeople at this retail brand name has built a better shopping experience □ □ □ □ □

I find events of this retail brand interesting in the sensory way □ □ □ □ □

Stories of this brand stimulate my curiosity □ □ □ □ □

Section 5: Perception of supermarket image


supermarket named in your answer to Question 4, Part 1)




Store image

The supermarket offers high-quality merchandise □ □ □ □ □

All brands you planned to buy were available □ □ □ □ □

Physical facilities are visually appealing □ □ □ □ □

It is easy to find products on promotion □ □ □ □ □

Employees are well informed, courteous and supportive □ □ □ □ □

The layout of this store is attractive □ □ □ □ □

The atmosphere in this store is pleasant □ □ □ □ □

Corporate image

This company has a good image among consumers □ □ □ □ □

346

I have a good image about the company □ □ □ □ □

This company has a good image compared to other competing companies □ □ □ □ □

Corporate social responsibility

The supermarket respects and protects the natural environment □ □ □ □ □

They contribute money to cultural and social events □ □ □ □ □

This supermarket treats its customer honestly □ □ □ □ □

This supermarket makes an effort to know customers’ needs. □ □ □ □ □

This supermarket offers safety at work to its employees □ □ □ □ □

This supermarket treats its employees fairly (without discrimination and abuse0) □ □ □ □ □

Section 6: Other features of supermarkets Note: as above


5, where 1 means “strongly disagree” and 5 means “strongly agree”


Trust

I trust this retailer □ □ □ □ □

I consider that to shop in the stores of this retailer provides a guarantee □ □ □ □ □

I believe that this retailer is honest/sincere toward its consumers □ □ □ □ □

This retailer regularly renews itself to meet the needs of its consumers □ □ □ □ □

Habit

I have been shopping at this supermarket for a longtime □ □ □ □ □

I have no need to think about shopping at this supermarket □ □ □ □ □

I do it without thinking (being used to where the products I need are located , and in many convenient ways)

□ □ □ □ □

Store accessibility

I can get to store X quickly □ □ □ □ □

I can get to store X without problems □ □ □ □ □

I can get to store easily □ □ □ □ □

Alternative attractiveness

Probably, I would be satisfied with another company □ □ □ □ □

There are other good companies to choose from □ □ □ □ □

I need to change the place for shopping, there are other good department stores to choose from □ □ □ □ □

I would be more satisfied with the products and services of other department stores □ □ □ □ □

Switching costs

Switching to other providers will bring economic loss □ □ □ □ □

Switching to other providers will bring psychological burden □ □ □ □ □

Search and evaluate the untested service department store costs you time and effort □ □ □ □ □

An uncertain feeling is relative to the untested service department store □ □ □ □ □

In general, it will be a hassle switching to another provider □ □ □ □ □

If I switch to a new brand name, I will miss some of the services and benefits of the loyalty programme from this brand name (mileage and membership service)

□ □ □ □ □

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Section 7: Demographic information

1. Where do you live?

Ha Noi Da Nang Ho Chi Minh

Binh Duong Can Tho

2. Please choose your gender:

□ Male □ Female □ Other

3. Please choose your job:

Student

Self employed

Office staff

Housewife

Unemployed

Other

4. Your monthly income

Lower than 5 million VND

5-10 million VND

10-20 million VND

20-50 million VND

Higher than 50 million VND

5. How much does your household spend monthly on grocery shopping?

Lower than 5 million VND

5-10 million VND

10-20 million VND

More than 20 million VND

Loyalty programmes

I save money □ □ □ □ □

Collecting points is entertaining □ □ □ □ □

When I redeem my points, I feel good about myself □ □ □ □ □

I belong to a community of people who share the same values □ □ □ □ □

They take better care of me □ □ □ □ □

I feel I am more distinguished than other customers □ □ □ □ □

Promotion effect

I think all promotional activities of this supermarket are persuasive and have a positive effect □ □ □ □ □

My purchasing willingness rises as a result of the promotional activities □ □ □ □ □

It is well worth going shopping during the period of a sales promotion □ □ □ □ □

348

6. Your age range:

Under 18 18-22 23-30

31-40 41-55 Above 55

7. Your education level:

GCSE’s A levels College, undergraduate Postgraduate

If you would like to receive a report of findings from this survey, please provide us your

contact details. We understand and respect your rights to privacy.

Name :

Mailing address:

Thank you for your participation

With kind regards,

Thi Diem Em Nguyen

349

Appendix 3.5 - Measurement variables used from Section 2 to Section 6 in the

questionnaire (Phase Two) and code book for other questions used in questionnaire

Section 1 of questionnaire

Coding is presented in “BOLD” style as bellow:

Q1: Overall, where do you prefer to go for grocery shopping?

1 = Supermarkets

2 = Traditional markets

3 = Other

Q2: How often do you go to traditional markets?

1 = Once a day 2 = Twice a week 3 = Three times a week

4 = Once a month 5 = Twice a month 6 = Other

Q3: How often do you go to supermarkets?

1 = Once a day 2 = Twice a week 3 = Three times a week

4 = Once a month 5 = Twice a month 6 = Other

Q4: Which supermarket do you usually go? (Please just choose one option)

1 = Co.opmart or Big C

2 = Lotte Mart

3 = Vinmart

4 = AEON

5 = Other, please name it __________

Q5: Do you have any loyalty cards from the supermarket which you have just chosen at

Question 4?

1 = Yes

2 = No

Q6: How long have you used it?

1 = I have no loyalty card

2 = Less than 1 year

3 = 1-3 years

4 = More than 3 years

Q7: Do you think that you are loyal to the above chosen supermarket (question 4)?

1 = Yes

2 = No

Q8: How satisfied are you with the above chosen supermarket on a scale of 1 to 5? (1 means

“very dissatisfied”, 5 means “very satisfied”)

1 = 1

350

2 = 2

3 = 3

4 = 4

5 = 5

Q9: How satisfied are you with the offered service quality by this supermarket on a scale of 1

to 5? (1 means “very dissatisfied”, 5 means “very satisfied”)

1 = 1

2 = 2

3 = 3

4 = 4

5 = 5

Q10: Do you think your favorite supermarkets meet your needs?

1 = Yes

2 = No

3 = Partly met

Q11: If you are not satisfied with the service or the quality of the products at a supermarket,

will you back to visit and shop there again?

1 = Yes

2 = No

Q12: Will you still stay with your favorite supermarket if you see an alternative attractiveness

from other supermarkets?

1 = Yes

2 = No

Q13: “I choose this supermarket’s brand name because its good store image”. Do you agree

with the above statement?

1 = Yes

2 = No

Q14: Do you think loyalty programs such as bonus points, discounts and gifts will affect your

decision?

1 = Yes

2 = No

Q15: If other supermarkets offer appeal promotions or discounts, would you be ready to

switch to them?

1 = Yes

2 = No

Q16: How many loyalty cards do you have for grocery shopping from different supermarkets?

1 = 0

2 = 1

3 = 2

4 = 3

5 = More than 4

351

Q17: Suppose you are always loyal to specific supermarket A, if supermarket B opens a store near

you or easier for you to get there and suppose that other factors meet your requirements, do you

wish to switch to shop at supermarket B?

1 = Yes

2 = No

Q18: Does the supermarket’s brand name affect your choices?

1 = Yes

2 = No

Q19: Suppose that there are two different supermarkets that you feel satisfied, all other factors are

the same, one of these is a domestic brand name, another is foreign brand name, which one will

you choose?

1 = Domestic brand name

2 = Foreign brand name

Q20: Are you in charge with buying grocery products for the whole family or for yourself?

1 = The whole family

2 = Myself

3 = I am not in charge with buying grocery products

Coding for measured variables is presented as followed:

Manifest variables Sources

Customer

perceived value

CPV1 Products are valuable

Chang and Wang (2011) CPV2 Prices are fair


CPV4 Compared to the price we pay, we get reasonable quality Eggert and Helm (2000)

CPV5 Compared to the quality we get, we pay a reasonable price

CPV6 The purchasing relationship delivers us superior net-value.

Customer

satisfaction

CS1 Complete service offered by a supermarket is significantly above expected Kitapci (2013) CS2 In general, my satisfaction level related to the supermarket that I have already dealt with is high


the supermarket

CS4 Shopping at the supermarket has been an enjoyable experience Lin (2014), El-Adly (2016)

CS5 I am disappointed to have been in this store Bouzaabia (2013)

Customer loyalty

CL1 In the near future, I am sure to repurchase at this supermarket and buy more at this one than at

another retailer

Swoboda (2013)

CL2 I am willing to pay more as compared to other retailers for the products I buy from this retailer Srivastava (2016)

CL3 I will say positive things about the retailers and recommend it to others Srivastava (2016), El-Adly (2016)

CL4 I would consider the supermarket my first choice to do shopping Lin (2014), Terblanche (2018)

CL5 I will always continue to choose the products of this grocery store instead others Oliver (1997)

In-store logistics


Bouzaabia (2013)



ISL4 In this supermarket, sufficient carrier bags are provided by the cashiers

ISL5 In this supermarkets, all products can be easily reached

ÍSL6 Prices on the product labels are correct

ISL7 The sell-by date is well indicated on the products

Service quality

SQ1 I would say that the quality of my interaction with the provider’s employees is high Liu et al. (2011) SQ2 I always have an excellent experience when I interact with my service provider

SQ3 I feel good about what my service provider provides to its customers.

SQ4 Service employees at this store have good product knowledge

Jiang et al. (2018) SQ5 Service employees at this store are willing to help customers

352


E-service quality

ESQ1 Organisation compensates me when what I ordered does not arrive on time

Zemblyte (2015)

ESQ2 Organisation picks up items I want to return with minimum hassle

ESQ3 Organisation makes accurate services (accurate records of consumers, accurate account, etc..)







ESQ10 My order is quickly confirmed and kept by the organisation

Product quality


Jiang et al. (2018) PROQ2 Products in this store are of consistent quality


PROQ4 Products in this store are of good design

Price

PRICE1 Goods at this store are reasonably priced Jiang et al. (2018)

PRICE2 The prices of the products in this supermarket are cheaper than others Emi Moriuchi, 2016

PRICE3 Goods at this store offer value for money Jiang et al. (2018)

Customer service


Kursunluoglu (2014)

CUSER2 Having clean restrooms


CUSER4 Having easy product return policy

CUSER5 Always having an available slot in the car park

CUSER6 Broadcasting nice music inside the supermarket

CUSER7 Providing noiseless shopping possibility

CUSER8 Having informative in-store employees in encounter stage

CUSER9 Having a beautiful gift wrap

CUSER10 Doing demonstrations about how to use the product

Customer

experience


Srivastava (2016)



CUSEXP4 I did not feel deceived by the service staff (such as pricing, special deals, discounts, gifts etc)

Retail brand

experience


Khan and Rahman (2016)


RBEXP3 Point-of-sales contact produces a strong impression on my intellect



RBEXP6 Stories of this brand stimulate my curiosity

Store image


Bouzaabia (2013)



STIMA4 It is easy to find products in promotion

STIMA5 Employees are well informed, courteous and supportive

STIMA6 The layout of this store is attractive Jiang et al. (2018)

STIMA7 The atmosphere in this store is pleasant

Corporate image

COIMA1 This company has a good image among consumers Calvo (2015) COIMA2 I have a good image about the company

COIMA3 This company has a good image compared to other competing companies

Corporate social

responsibility

CSR1 The supermarket concern with respecting and protecting the natural environment

Perez (2015) CSR2 They contribute money to cultural and social events




CSR6 This supermarket treats its employees fairly (without discrimination and abuses)

Trust


Lombart (2014) TRUST2 I consider that to shop in the stores of this retailer is a guarantee


TRUST4 This retailer regularly renews itself to meet the needs of its customers

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Section 7 of questionnaire (demographic information)

Coding is presented in “BOLD” style as bellow:

LOCATION = Where do you live?

1 = Ha Noi 2 = Da Nang 3 = Ho Chi Minh

4 = Binh Duong 5 = Can Tho

GENDER = Please choose your gender

1 = Male

2 = Female

3 = Prefer not to say

OCCUPATION = Please choose your job

1 = Students

2 = Self employment

3 = Office staffs

4 = Housewife

5 = Unemployment

6 = Other

Habit


Olsen (2013) HABIT2 I have no need to think about doing (shopping at this supermarket)


ways)

Store accessibility

STAC1 I can get to store X quickly Swoboda (2013)

STAC2 I can get to store X without problems


Alternative

attractiveness

ALA1 Probably, I would be satisfied with another company Calvo (2015)


ALA3 I need to change the place for shopping, there are other good department stores to choose from Tung (2011)


Switching costs

SWC1 Switching to other providers will bring economic loss Liu et al. (2011)


SWC3 Search and evaluate the untested service department store costs you time and effort Tung (2011)


SWC5 In general, it will be a hassle switching to another hotel Qui et al. (2015) SWC6 If I switch to a new brand name, I will miss some of the services and benefits by the loyalty program

from this brand name (mileage and membership service)

Loyalty programs

LPRO1 I shop at a lower financial cost (I save money)

Stathopoulou (2016) LPRO2 Collecting points is entertaining



LPRO5 They take better care of me

LPRO6 I feel I am more distinguished than other customers

Promotion effects

PROE1 I find the promotional activities of this online supermarket to be very persuasive and positive Emi Moriuchi (2016)

PROE2 My purchasing willingness arises from the promotional activities Tung (2011)


354

INCOME = Your monthly income

1 = Lower than 5 million VND (170 GBP)

2 = 5-10 million VND (170-340 GBP)

3 = 10-20 million VND (340-680 GBP)

4 = 20-50 million VND (680-1700 GBP)

5 = higher than 50 million VND (1700 GBP)

FAMILY’S EXPENDITURE = How much does your household monthly spend on grocery

shopping?

1 = Lower than 5 million VND (170 GBP)

2 = 5-10 million VND (170 - 340 GBP)

3 = 10-20 million VND (340 – 680 GBP)

4 = more than 20 million VND (680 GBP)

AGE = Your age range

1 = Under 18 2 = 18-22 3 = 23-30

4 = 31-40 5 = 41-55 6 = Above 55

EDUCATION = Your education level

1 = GCSE’s 2 = A levels

3 = College/undergraduate 4 = Postgraduate

Appendix 4.1 – Some more direct quote of supermarket’s consumer interviewing in

Phase One

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Question 2: Do you often go to the supermarket? How many times a week?

BD2_F30 go to shop at a supermarket every day because she is working in the

supermarket, she stated, “I work at that supermarket, so I buy fresh food daily and other

consumption products here after finishing my daily job, I am so happy and always choose

supermarkets, I have no time to go to traditional markets”.

HN4_26 stated, “My family usually goes to supermarkets together, twice a month to buy

long-term-used consumption products and spend around six to seven million VND (200-250

GBP) each time. I think a supermarket that I choose to shop, named Lotte is much expensive

compared to other one, but I believed products provided with such amazing quality, most of

them are foreign brand name, I prefer toothpaste, shower gel, foreign household utensils here,

sometimes we also buy imported fresh fruits and fresh meat”.

DN2_F35 stated, “I go to a supermarket normally twice a month to buy milk and cheese

for my baby, when I go there to buy these special products, I buy consumption stuffs as well, I

have never wanted to buy milk the traditional markets, I think that buying milk should be done

at supermarkets, especially, foreign brand name because I believe their guaranteed quality and

there are also a variety of choices and price”

Question 3: Do you prefer shopping at supermarkets or traditional markets? Why?

DN2_F35 showed her trust in supermarkets by saying “I always choose to shop at a

supermarket because I think that the quality of products here has been guaranteed, especially

milks which I usually buy for my children, I have always been suspicious about the quality and

origin of dairy products being sold outside and at traditional markets”.

HCM6_33 stated, “I prefer shopping at supermarkets as no one feel annoyed if I do not

buy anything after checking for a while, I feel comfortable and relaxed, especially, I always

know how much I am going to pay, I am happy to check and take products back if I feel I do

not need or in the case I do not bring enough money”, BD3_F26 stated “I prefer to shop at

supermarkets because they clearly state products’ origin, expire date and price, I feel safe with

foods here. In addition, there are many promotion programs that I can consider to choose

between two different types of brand name”

However, there are some consumers preferring shopping at traditional markets such as

CT1_M27, HN3_M24, CT3_M53. They explained some disadvantages of shopping at

supermarkets and reasons why they choose traditional markets. CT1_ M27 said: “I think

shopping at traditional markets is very convenient, it is near my house and I just drive my

scooter to there and get what I want immediately; I do not need to wait for parking or long-

queuing when checking out. Besides that, many fresh vegetables and meats are available there.

Many special home-made products and some kinds of nice fishes are not sold in supermarkets.

However, sometimes I am suspicious about the quality of meats or their origins; I usually go

356

to specilised meat shops to shop separately. In general, I feel free to shop at traditional

markets, easy to buy and choose”.

HN3_M24 said, “It is very convenient to shop at traditional markets, it is near my house,

products’ prices at traditional markets are cheaper, I do not usually buy a lot, so supermarkets

are not a choice for me. However, sometimes I go there with family in the weekend to enjoy

going around and using other services offered such as cinema, fast foods”

CT3_M53 stated, “Regarding buying daily food, I prefer to go traditional markets because

fresh and delicious food is sold here every day, in supermarkets I feel that fish and vegetables

might be presented there a little longer than at the traditional market. However, when I need

to buy clothes, I choose supermarkets because as you know, I am a man, going to the

traditional markets and buying is not convenient, in Vietnam, a man might not go to markets

and choose clothes for himself, wife is doing these things, people might notice if I go there, I

feel not comfortable, but with supermarkets, no one is going to notice. In addition, in-store

staffs in a supermarket are not chasing me to buy, I feel uncomfortable with chasing-to-sell

things which usually happen at the outside shops”

HCM4_F45 prefer both, depending on situation, “If I just buy some products with a small

amount, I will choose traditional market because buying transaction is faster, I do not have a

lot of time, when I need something, I run to the traditional market which is 200m away from

my house, very convenient. I choose to buy long-term used products at supermarkets such as

toothpaste, household products, salt, sugar, toilet roll, shower gel. And I just do it when I have

a plenty of time, normally at evening”

Question 4: Mentioning supermarkets, which one is in your top of mind? Why? Is it

always your top choice?

CT1_M27 stated, “Considering supermarkets, my top of mind is Coopmart, because it is a

first supermarket established in my city, my mom and I always go there for shopping, I think

that I will not change my habit, always choose Coopmart, I trust the firms more when they

show their social responsibility, such as sponsoring many youth activities in my university and

spending money to help narrowed families in my province”. HCM4_F45 stated, “I think about

Auchan supermarket immediately and I always choose to shop there because it is next to my

house, very convenient. More than that, I am happy with in-store staffs here, they show their

respect to me and they are really supportive when I asked them to find products that I need,

in-store decoration makes me feel relaxed and very comfortable, compared to the

uncomfortable feelings perceived from other supermarkets with complicated decoration and

close shelves allocated”.

HN3_F24 explained more about why she always stays with her favorite supermarket, “I

choose Big C because its long business history, I trust the way they are doing their business,

if I drive my scooter one to two kilometers more, I can easily find other supermarkets but their

brand names could not give me the feeling of trust”.

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Question 5: Can you tell me the main purpose of going to this supermarket?

HCM4_F45 “I buy many items that can be used for a long time, including: discounted item

such as paper towels, soap, shower gel, toilet cleaning products; ingredients for cooking.

Besides that, if I have a free time, just go there to enjoy a fresh atmosphere and have lunch

with my children”. Another respondent said “I go to a supermarket 3-4 times a week to buy

meats, fishes and vegetables for daily cooking, going around and checking many new

products even I do not intend to buy is also my favourite thing to do. I do not care about

many entertainment services attached in supermarkets due to no demand as getting older,

I seem to be not interested to cinema or beauty services offered”- HCM5_F60

Question 6: Which factors influence your loyalty to the supermarket? Please list at

least 5 factors in descending order of preference?

For example, HCM3_F35 stated, “For me, origin of products is the most important thing,

I do not really care about prices charged because I think “the quality of products might

depend on how much you pay for”, I am happy to pay more if I know a clearly stated origin

and good quality. Besides that, I do care about supermarket brand names, I believe that it

takes them a lot of time to build that such amazing brand name; I trust them who will not

offer low quality products which can destroy their brand names. To be honest, this

supermarket is far away from my house, I go there by car with family at the weekend, but

getting a good-quality product with a trusty foreign brand name, I am still happy even this

issue costs me more money to get there”.

BD1_F18 stated, “I am currently a student and live far away from my home town, I need

to cook for myself, I am loyal to a supermarket near my house named Vinmart because of

its convenient location which on the way to go my university, this one is premium

supermarket, it charges more for every single products offered but I am happy with that

because I think that the product quality is far more better compared to other cheap

supermarkets, I can buy a fresh organic vegetables and meats everyday here”.

HCM6_F33 stated, “Products’ price, promotion programs, layout and the order of shelves

allocated are very important to me, I find more comfortable if supermarkets’ shelves are

allocated far apart from each other, it makes me easy to choose products. The one that I

am loyal to could not offered a nice ordered shelves but other factors might be suitable to

me, so I still decide to be loyal to them”.

HN1_F24 explained, “I have just graduated from a university, and being looking for a job,

so I have a really tight budget, currently I am loyal to BigC because it offers an affordable

price and comparative quality, I am happy to shop there. However, in the future, if I have

more money, I might prefer to choose to shop at premium supermarkets”.

HN2_F30 who stay at luxury apartment in a new urban area presented that products’ quality

and convenient location accessibility are the most important factors in her case, she stated

that “I am currently a full-time office staff, I have no time to go for shopping, I need to pick

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up my baby every afternoon at 5:30 pm, after considering products’ quality, the advantage

of nice location is a reason I always choose Vinmart as it is located near my building. I

have a quick shopping there every afternoon. Other grocery and consumption products, I

will do it at the weekend at a bigger store, the same brand name (Vinmart) as well because

I trust them, the Vingroup built this new urban city, with good reputation and long-

business history in Vietnam, their supermarket brand name is Vinmart, everything I need,

I can buy in this area, why not be loyal to them?”.

HN5_F56 also choose Vinmart to be loyal to because Vinmart have a variety of product

ranges and promotion program, a premium price is not a problem for her, she prefers to

buy there because of big size supermarket which allows her to enjoy shopping there. In

addition, she is currently a housewife, obtaining points as conducting any purchase is also

here favorite thing, she stated “accumulating points and getting a reward later stimulate

my purchase, sometimes I just need to buy around 300,000 VND (10 GBP) but that the

offer is buying 20 GBP and get a free gift or double-point offered at a specific day

stimulate me to buy more. In the end, I usually buy more than what I intended to buy”.

HCM5_F60 also have the same point of view, “When I buy products in Coopmart,

accumulated points will be rewarded later, three months or at the end of the year, I got a

really nice gift from them, thanks for being loyal, I was so happy last year when they sent

a gift to my house. Although the value of a received gift is not high, the feeling of getting

free gift made me feel happier. I think that all older people might have the same feeling

like me. Besides that, for me habit is very important factor. I am 60 years old now, I am

afraid to change and being used to with everything inside the supermarket. For example,

I know where the products I need are located, I can easily reach them, by this way, I can

save a lot of time”.

HCM4_45 added some more information about promotion programs “for some products,

if a supermarket gives a huge discount, I will buy more and store them in my house, I am

going to buy less and just enough to use in a short-term, wait for a next promotion

campaign if I can not get a good deal”. She also explained that stable prices charged is

also her criteria, “I do want to shop at supermarkets which constantly adjust their

products’ price, increase prices when they have a hot item or the demand of consumers is

high, Auchan offered a bit higher price compared to other supermarkets but they keep

their product prices stable”.

Question 7: What factors affect your satisfaction with the supermarket?

CT2_F35 stated, “I used to shop at BigC when it is first established in my city, but I had

a bad experience with not very friendly staffs there, so I have decided to shop at Coopmart

where staffs are more friendly and always support me with their happy faces and smiles,

even Coopmart is far from my house compared to easily reached BigC, I still choose

Coopmart”. HN4_26 added, “I think that the consultant way of in-store staffs is very

important. I can say that all staffs at my favorite supermarkets are so nice, they walked

me to the shelves to find stuffs with their smiling faces”.

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CT3_M53 considered that price is not the important factor when considering his

satisfaction, in-store logistic should be mentioned; he said, “I like that supermarket because

all shelves are logically allocated, it makes me easy to find products that I need”. DN4_F19

stated that “to make me satisfied, product quality is the most important factor, then

problems solved quickly by in-store staffs should be considered”. DN2_F35 said, “if other

factors are the same, I might choose and be happy with supermarkets where I can pay for

my products easier and quicker”.

HCM6_F36 stated that “Free home delivery service from my favorite market is very

convenient to me as I always buy a large amount of products, I knowing their policy is to

offer this free service when you buy more than 500,000 VND (17 GBP) within 7 kilometers.

However, that time I bought 4 million VND (130 GBP), they were so flexible to send the

items to my house”.

Question 8: Tell me the experience you have/ have not enjoyed about the service at

the supermarket you have been before?

HCM6_F33 told, “The promotion program is generally written, so I was very confused.

For example, consumers will get a free gift item if they buy more than 300,000 VND

(approximately 10 GBP). I bought more than 900,000 VND (nearly 30 GBP), I requested

for having 3 gifts, but cashiers said no to me and I wanted to split the bills, they were not

flexible to solve these problems for me and cannot accept splitting the bills as well as

giving me a three free gifts. I think in this case, they should clearly state the condition of

this promotion program as well as being more flexible to support me”.

HN3_M24 said “I still remember that when I chose the discount product, 30% discount

with the final price is 100, 000 VND, I bought many different items and forgot to check

when they gave me a bill. When I backed home, I realized that that item was not selling

with a sale price because there was no sale barcode in there. I think that some consumers

take the new one to this area and no staffs came there to check. I was confused and paid a

higher price than I expected. I felt not happy about that”.

Besides that, HCM3_F35 said “the only place for payment is located at the first floor, I

drove my car and parked it the third floor and just need to buy some household utensils

there, it took time for me to go down to the first floor and back to the third floor. I suggest

the supermarket should have checkout areas at each floor”.

BD2_F30 shared “that supermarkets slightly change a product price in the upward

direction, but the system has not updated as well as supermarkets have not put a new price

on displayed products makes consumers so annoyed when they pay”.

HN4_F26 complained that in-store staffs were not proactively introduce their promotional

programs to her “when I checked out, they did not tell me if I buy more than one million

VND (33 GBP), they will give me a 5% direct discount at that day, I could not save my

money as I bought 970,000 VND. I felt so regret”

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Question 11: In your opinion, how does store image affect your purchasing’s

perceptions and your satisfaction?

HCM6_F33 stated “store image has a significant effect to my satisfaction and purchase

perception, the good decoration as well as a layout of how well products being allocated

makes me feel comfortable, I will buy more. My current supermarket arranges products

logically, for example, next to dry food stalls like noodle, soy sauce will have condiments,

canned food. If the supermarket constantly changes their store layout, I might feel

disappointed as I could not easily find items”, HN5_F56 “store image is very important, if

supermarkets are spaciously and logically decorated, I feel better, when mention about store

image, I immediately think about how I feel about store when shopping”, HN4_26

emphasized that “the main theme color covered inside supermarkets is very important,

consumers might feel good with specific color, such as green, blue or red”, BD3_F26 “if

that supermarkets have a good store image, clean and fresh atmosphere make me trust them

more and might stimulate my purchasing decision, if a store is decorated in cramped

conditions, I will not go there, I still have a plenty of choices”.

BD2_30 “I suppose that store image is a crucial factor as considering my purchase decision,

it decides that whether should I spend money to buy products or not, spacious walkways are

important, one more thing I can say, my favorite supermarket has a way and toilet for

disable, I think they are really thoughtful, I do appreciate this thing”. CT3_M53 added that

“Besides a logical and eye-catching store decoration, that how well in-store staffs treat me

is also important, if the two presented factor happen, I will pay more because I feel satisfied.

To me, product price is not the main factor”. HN3_M24 “Supermarket A always plays a

relaxing music, easy to hear, the main color in the shop is not too glamorous, I feel

comfortable, I will never shop at supermarket B again because it is too bright”

Question 13: Does corporate image affect your choice in choosing which supermarkets

to go?

HN2_F30 “The positive feeling of corporate image creates my trust and commitment. For

example, Vinmart supermarket is from Vingroup which is a biggest group in Vietnam

investing into many projects and fields such as real estate, hospital, university and school

with trusty reputation, when I think about Vinmart, I think about premium quality with fresh

meats, clearly stated product origin and organic vegetables it does really affect my choice”.

BD3_F26 presented “corporate image creates a credibility of that business, it is a first

criteria when I choose which supermarkets to go”. HCM1_M60 “Considering a corporate

image, my favorite supermarket gives me a safe and peaceful feeling when their marketing

campaigns always emphasize how their consumption products build happiness within

families. I think that they are so smart as using family-focused emotional marketing videos”.

CT1_M27 emphasized “If firms cannot create a good image, I will never choose them. For

example, I do not supermarket A because they have a bad image, people keep telling me

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about the not clearly stated origin of products offered and sometimes they offer an expired

product with good deal but I think that it is so immoral”. DN3_M18 added “if I need to

choose one between two different supermarkets which are a new-developed supermarket

and well-developed and trusty supermarket, I will go for the second one because it takes

supermarket a long time to build their images, I do not want to give a try with untested

one”.

Question 14: Does corporate social responsibility affect your choice in choosing which

supermarkets to go?

HCM4_F45 presented “If supermarkets pay their employees a lower wage compared to

what that position expected to be paid and firms not paying taxes, I will stop shopping

there, even I am satisfied with all other things, I might choose different brand names, even

it might be far away from my house”

Question 15: Do you think loyalty programs such as bonus points, discounts and gifts

will affect your decision?

HCM4_F45 clearly stated, “There are a plenty of supermarkets which are located near my

house, but I still choose supermarket A because I got a loyalty card there 5 years ago,

currently, every single transaction above 1 million VND (approximately 33 GBP), I will

get 5% off compared to other supermarkets which currently offer accumulating points or

lower-rate discounts, thanks to being a long-term loyal customer, I got such an amazing

deal, even supermarket A is not near my house, I definitely always choose them and

encourage my family and other friends to shop there as well”.

Question 17: Suppose you are always loyal to specific supermarket A, if supermarket

B opens a store near you or easier for you to get there, do you wish to switch to shop

at supermarket B?

DN2_F35 stated, “if supermarket B offers an equal product quality compared to

supermarket A, I will move to supermarket B because I can save much time”, CT3_M53

added “each supermarket has its own strength but I would give supermarket B a go and

reconsider after shopping there”. However, there are some participants explained “I will

not switch to supermarket B because I get used to with where my needed products are at

supermarkets A, habit is more important. If consumers buy many products at the same time,

I think that location might be not a big problem for them” (HN3_M24).

Question 18: Do you concern about online service at supermarkets such as online

ordering or home delivery, consulting chat? What do you want from supermarkets’

online service?

HN6_F33 stated that “To be honest, online services at supermarkets in Vietnam have been

very ineffective, because consumers normally want to look at a needed product and pay on

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the chosen items, they are so afraid of low product quality if shopping online happen,

especially with fresh fruits and meats and vegetables”. CT2_F35 noted, “I do not care

about this service at a supermarket because in-store shopping time makes me feel more

comfortable and I can spend a good time with family there as well”. “With an online

service, supermarkets always set a minimum amount of money that consumers spend in

order to deliver to consumers’ house, I do not usually buy a lot. In addition, last time when

I checked a supermarket A’s website, I feel that the interface was not eye-catching, they

did not update details on pricing, product description as well as size of products in the case

I wanted to buy fruits. So, I do not care about these services. Currently, I am still vague

about whether other supermarkets have online services or not” DN1_F24 said.

Question 20: Do you think the price at this supermarket is reasonable?

HCM4_F45 stated, “I have not compared the prices between supermarkets, I think that my

current chosen supermarkets offer a bit slightly higher price, but I do not care much, above

all other things, I feel respected as all of in-store staffs at the supermarket have treated me

so well, I feel extremely satisfied”

Question 21: Your ideas about customer service at this supermarket? Can you tell me

what things you are satisfied and not satisfied with their customer service?

CT2_F35 narrated “I feel satisfied with their consumer services such as free parking fee,

fresh shopping atmosphere provided, quick checkout process with staffs always smiling,

clearly noted that how to use products, friendly and supportive staffs, free wrapping service

offered. I have never experienced any unsatisfied thing there”. HCM4_F45 stated, “I did

buy a washing machine there and there were some technical problems occurred after one

week of using, I contacted to a supermarket and they offered me such quick and amazing

service to solve my problems. I feel happy about that and I always choose them”. HN2_F30

stated, “I am happy with the way how supermarkets solve occurred problems, when I paid

for my shopping, the price charged was different with the stated prices that I saw on

products, I claimed it and managers immediately came to the cashier to check and happily

solved my problem and not forget to give me an excuse as keeping waiting that long”.

Question 22: When you shop at the supermarket, how do you feel? (Relaxed,

respected, enjoyable?)

HCM6_F33 “I feel freedom and comfortable as having much time to go around, it is not a

tight squeeze, nice music played stimulate my purchase decision, compared to rushed

shopping behaviors at traditional markets each morning, I feel more relaxed with

supermarkets”.

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Question 23: What do you think about the brand? (Retail brand experience). Please

tell me more about your brand experience?

HCM4_F45 “the retail brand name gives me the feeling of trust as their stores are always

clean, fresh, spacious and friendly decorated. They have created a nice shopping space

which provides a pleasure and better shopping experience”.

CT1_M27 always feel good about his current chosen supermarkets as considering their

brand name, he explained “Its high prestige with high social responsibility, unified system

within supermarket chain, long history and good services and products offered make me

trust them more and enjoy a comfortable feeling when shopping. The belief is far more

compared to other factors, I have ever seen any brand name created and built better as my

current one”.

CT1_M27 always feel good about his current chosen supermarkets as considering their

brand name, he explained “Its high prestige with high social responsibility, unified system

within supermarket chain, long history and good services and products offered make me

trust them more and enjoy a comfortable feeling when shopping. The belief is far more

compared to other factors, I have ever seen any brand name created and built better as my

current one”.

Question 24: Give me your comments about their in-store logistic services? (The

shelves are well-stocked, easy returning, all products can be easily reached, enough

shopping carts, correct prices on the product labels..)

HCM5_F60 said, “constantly checking products on shelves and supplementing new

products have made a big difference between supermarkets, I might feel frustrated if I saw

the information of temporarily out-of-stock products”.

Question 25: Are you loyal to that supermarket brand? Please rank from 1 to 5 (1

means “very loyal”, 5 means “not very loyal”)

CT3_M53 explained, “That I am loyal to supermarket X is not because I am completely

satisfied with services and products offered, it is all because of its convenient store

accessibility and habit, in the future, if there are some alternative choices, I might consider

and experience other brand names”. HN3_M24 added “My chosen supermarket is not the

best choice, I know, but I accept it and happy, but I need to admit that my loyalty level is

not high, I am happy to try other supermarkets if needed”.

HCM2_M28 said “Although I have a loyalty card but I always forgot it at home and have

no interested in accumulating points, for me convenient factor is the most important, I

usually move around supermarkets for shopping, each supermarket has its own advantages

and strength, I might not commit myself with any supermarkets”.

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Question 26: Are you satisfied with the offered service quality? How satisfied are you

on a scale of 1 to 5? (1 means “very dissatisfied”, 5 means “very satisfied”, did staff

respond enthusiastically when you asked?)

HN5_F60 narrated, “My apartment is located at 25th floor, I always buy many items at a

supermarket which is under my building and their service staffs help me bring these stuffs

to my apartment, sometimes I bought grocery products and asked them send it to my son

house which is 5 km away from their current store, they still offer me free delivery. Of

course, I bought more than 700,000 VND each time (approximately 23GBP). I am so happy

with this amazing service”.

Question 30: “I choose this supermarket’s brand name because its good store image”.

Do you agree with the above statement?

HN4_F26 said, “Store image is not a main factor why I choose a supermarket to go for

grocery shopping, there are a plenty of other crucial elements. However, if I say that store

image do not influence my choice, maybe it is wrong too. If I need to rank a number of

important factors which affects my choice, store image will be placed at the end of the list”.

BD2_F30 stated that the above presented statement provided by the interviewer is wrong

“because store image partly affects my choice, thanks to its convenience, I choose it”

Question 31: Suppose that there are two different supermarkets that you feel satisfied,

all other factors are the same, one of these is a domestic brand name, and another is

foreign brand name, which one will you choose? Why?

HN2_F30 said, “The foreign brand name seems to be really attractive, posh, considering

psychological factor, I feel more confident to shop without constantly checking where

products come from. Besides that, my experience proves me that a foreign firm has

comprehensively and properly invested their stores and attached services provided, such

as spacious parking areas, spacious stores designed with logically allocated shelves and

decoration, for me, shopping there something like relaxing moment after a long-day work”.

Question 33: Where do you usually go for daily food and grocery?

HN2_F30 explained, “thanks to convenient attached services offered at my apartment,

supermarkets are located at every single building, I pop to the store and get my foods and

grocery products easily. I have no interested in shopping at traditional markets and other

private grocery stores”

Question 34: Are you loyal to a supermarket brand name or their specific store?

HN4_F26 said, “I am loyal to that specific store as it is near my house because I bought a

lot of things, it seems to be heavy and I might feel tired if I choose other stores.

Furthermore, I get used to with their decoration and which areas products are allocated,

habit is very important too, I save much time and feel more comfortable”.

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Appendix 5.1 – Results from Tests of normality

Tests of Normality

Kolmogorov-Smirnov

a Shapiro-Wilk

Statistic df Sig. Statistic df Sig.

CPV1 .234 2913 .000 .875 2913 .000

CPV2 .227 2913 .000 .878 2913 .000

CPV3 .236 2913 .000 .874 2913 .000

CPV4 .242 2913 .000 .865 2913 .000

CPV5 .240 2913 .000 .874 2913 .000

CPV6 .229 2913 .000 .888 2913 .000

CS1 .257 2913 .000 .882 2913 .000

CS2 .225 2913 .000 .876 2913 .000

CS3 .251 2913 .000 .872 2913 .000

CS4 .222 2913 .000 .890 2913 .000

CS5 .219 2913 .000 .848 2913 .000

CL1 .209 2913 .000 .893 2913 .000

CL2 .189 2913 .000 .915 2913 .000

CL3 .213 2913 .000 .891 2913 .000

CL4 .233 2913 .000 .889 2913 .000

CL5 .192 2913 .000 .903 2913 .000

ISL1 .240 2913 .000 .887 2913 .000

ISL2 .248 2913 .000 .878 2913 .000

ISL3 .232 2913 .000 .855 2913 .000

ISL4 .245 2913 .000 .846 2913 .000

ISL5 .251 2913 .000 .858 2913 .000

ISL6 .241 2913 .000 .876 2913 .000

ISL7 .247 2913 .000 .860 2913 .000

SQ1 .205 2913 .000 .895 2913 .000

SQ2 .220 2913 .000 .885 2913 .000

SQ3 .256 2913 .000 .871 2913 .000

SQ4 .207 2913 .000 .892 2913 .000

SQ5 .251 2913 .000 .876 2913 .000

SQ6 .240 2913 .000 .873 2913 .000

ESQ1 .226 2913 .000 .897 2913 .000

ESQ2 .204 2913 .000 .905 2913 .000

ESQ3 .215 2913 .000 .893 2913 .000

ESQ4 .210 2913 .000 .893 2913 .000

ESQ5 .223 2913 .000 .886 2913 .000

ESQ6 .219 2913 .000 .886 2913 .000

366

ESQ7 .199 2913 .000 .901 2913 .000

ESQ8 .213 2913 .000 .894 2913 .000

ESQ9 .212 2913 .000 .890 2913 .000

ESQ10 .202 2913 .000 .891 2913 .000

PROQ1 .268 2913 .000 .854 2913 .000

PROQ2 .271 2913 .000 .854 2913 .000

PROQ3 .236 2913 .000 .875 2913 .000

PROQ4 .234 2913 .000 .876 2913 .000

PRICE1 .248 2913 .000 .879 2913 .000

PRICE2 .187 2913 .000 .904 2913 .000

PRICE3 .220 2913 .000 .885 2913 .000

CUSER1 .187 2913 .000 .913 2913 .000

CUSER2 .213 2913 .000 .899 2913 .000

CUSER3 .191 2913 .000 .907 2913 .000

CUSER4 .206 2913 .000 .900 2913 .000

CUSER5 .240 2913 .000 .871 2913 .000

CUSER6 .228 2913 .000 .888 2913 .000

CUSER7 .237 2913 .000 .885 2913 .000

CUSER8 .213 2913 .000 .900 2913 .000

CUSER9 .190 2913 .000 .903 2913 .000

CUSER10 .209 2913 .000 .899 2913 .000

CUEXP1 .234 2913 .000 .879 2913 .000

CUEXP2 .227 2913 .000 .884 2913 .000

CUEXP3 .238 2913 .000 .874 2913 .000

CUEXP4 .245 2913 .000 .875 2913 .000

RBEX1 .209 2913 .000 .895 2913 .000

RBEX2 .230 2913 .000 .883 2913 .000

RBEX3 .199 2913 .000 .900 2913 .000

RBEX4 .228 2913 .000 .885 2913 .000

RBEX5 .211 2913 .000 .883 2913 .000

RBEX6 .213 2913 .000 .909 2913 .000

STIMA1 .230 2913 .000 .878 2913 .000

STIMA2 .222 2913 .000 .892 2913 .000

STIMA3 .228 2913 .000 .883 2913 .000

STIMA4 .256 2913 .000 .876 2913 .000

STIMA5 .228 2913 .000 .886 2913 .000

STIMA6 .221 2913 .000 .881 2913 .000

STIMA7 .241 2913 .000 .874 2913 .000

COIMA1 .254 2913 .000 .866 2913 .000

COIMA2 .254 2913 .000 .864 2913 .000

COIMA3 .227 2913 .000 .879 2913 .000

CSR1 .217 2913 .000 .882 2913 .000

367

CSR2 .226 2913 .000 .883 2913 .000

CSR3 .234 2913 .000 .875 2913 .000

CSR4 .247 2913 .000 .872 2913 .000

CSR5 .236 2913 .000 .868 2913 .000

CSR6 .220 2913 .000 .871 2913 .000

TRUST1 .261 2913 .000 .867 2913 .000

TRUST2 .270 2913 .000 .865 2913 .000

TRUST3 .250 2913 .000 .873 2913 .000

TRUST4 .248 2913 .000 .876 2913 .000

HABIT1 .245 2913 .000 .880 2913 .000

HABIT2 .222 2913 .000 .885 2913 .000

HABIT3 .234 2913 .000 .883 2913 .000

STAC1 .227 2913 .000 .879 2913 .000

STAC2 .233 2913 .000 .871 2913 .000

STAC3 .236 2913 .000 .868 2913 .000

ALA1 .194 2913 .000 .911 2913 .000

ALA2 .202 2913 .000 .901 2913 .000

ALA3 .200 2913 .000 .911 2913 .000

ALA4 .196 2913 .000 .907 2913 .000

SWC1 .192 2913 .000 .914 2913 .000

SWC2 .188 2913 .000 .916 2913 .000

SWC3 .200 2913 .000 .910 2913 .000

SWC4 .180 2913 .000 .911 2913 .000

SWC5 .183 2913 .000 .912 2913 .000

SWC6 .185 2913 .000 .905 2913 .000

LPRO1 .231 2913 .000 .886 2913 .000

LPRO2 .243 2913 .000 .875 2913 .000

LPRO3 .228 2913 .000 .879 2913 .000

LPRO4 .227 2913 .000 .882 2913 .000

LPRO5 .206 2913 .000 .892 2913 .000

LPRO6 .192 2913 .000 .902 2913 .000

PROE1 .245 2913 .000 .873 2913 .000

PROE2 .243 2913 .000 .871 2913 .000

PROE3 .250 2913 .000 .866 2913 .000

a. Lilliefors Significance Correction

368

Appendix 5.2 - Normal probability plots

370

Appendix 5.3 – Independent samples test (Non-bias response)

Independent Samples Test

Levene's Test for

Equality of

Variances

t-test for Equality of Means

F Sig. t df Sig. (2-

tailed)

Mean

Difference

Std. Error

Difference

95% Confidence Interval of the

Difference

Lower Upper

CPV1 Equal variances assumed 0.441 0.507 1.924 1454 0.055 0.085 0.044 -0.002 0.172

Equal variances not assumed 1.924 1453.716 0.055 0.085 0.044 -0.002 0.172



CPV3 Equal variances assumed 0.408 0.523 2.745 1454 0.006 0.121 0.044 0.034 0.207

Equal variances not assumed 2.745 1453.880 0.006 0.121 0.044 0.034 0.207







CS1 Equal variances assumed 0.204 0.651 1.278 1454 0.201 0.058 0.045 -0.031 0.146


CS2 Equal variances assumed 0.025 0.875 0.317 1454 0.752 0.014 0.043 -0.071 0.099


CS3 Equal variances assumed 0.090 0.764 -0.569 1454 0.569 -0.025 0.043 -0.110 0.060

Equal variances not assumed -0.569 1452.483 0.569 -0.025 0.043 -0.110 0.060

CS4 Equal variances assumed 0.202 0.653 -0.641 1454 0.521 -0.030 0.047 -0.123 0.062


CS5 Equal variances assumed 5.667 0.017 2.882 1454 0.004 0.181 0.063 0.058 0.305


CL1 Equal variances assumed 0.435 0.510 1.138 1454 0.255 0.056 0.049 -0.041 0.153


CL2 Equal variances assumed 0.743 0.389 3.008 1454 0.003 0.163 0.054 0.057 0.270








ISL1 Equal variances assumed 0.569 0.451 -0.284 1454 0.777 -0.015 0.053 -0.120 0.089




371





ISL5 Equal variances assumed 9.079 0.003 -2.541 1454 0.011 -0.121 0.048 -0.214 -0.028

Equal variances not assumed -2.541 1451.712 0.011 -0.121 0.048 -0.214 -0.028





SQ1 Equal variances assumed 1.540 0.215 2.396 1454 0.017 0.115 0.048 0.021 0.210


SQ2 Equal variances assumed 1.202 0.273 2.498 1454 0.013 0.114 0.046 0.024 0.204


SQ3 Equal variances assumed 0.332 0.565 0.063 1454 0.950 0.003 0.044 -0.083 0.089








ESQ1 Equal variances assumed 2.857 0.091 0.428 1454 0.668 0.022 0.051 -0.079 0.123












ESQ7 Equal variances assumed 0.513 0.474 -0.295 1454 0.768 -0.015 0.051 -0.116 0.085








PROQ1 Equal variances assumed 0.531 0.466 -1.350 1454 0.177 -0.063 0.047 -0.155 0.029








PRICE1 Equal variances assumed 0.186 0.666 -0.782 1454 0.434 -0.037 0.047 -0.130 0.056






CUSER1 Equal variances assumed 2.977 0.085 0.875 1454 0.382 0.049 0.057 -0.061 0.160


372

CUSER2 Equal variances assumed 0.040 0.842 -4.531 1454 0.000 -0.254 0.056 -0.364 -0.144

Equal variances not assumed -4.531 1453.977 0.000 -0.254 0.056 -0.364 -0.144



CUSER4 Equal variances assumed 0.026 0.873 -0.725 1454 0.468 -0.036 0.049 -0.132 0.061














CUEX1 Equal variances assumed 7.772 0.005 -0.059 1454 0.953 -0.003 0.047 -0.095 0.089








RBEX1 Equal variances assumed 3.396 0.066 1.847 1454 0.065 0.092 0.050 -0.006 0.190


RBEX2 Equal variances assumed 0.461 0.497 -0.029 1454 0.977 -0.001 0.047 -0.093 0.091








RBEX6 Equal variances assumed 1.198 0.274 -0.660 1454 0.509 -0.036 0.054 -0.142 0.070


STIMA1 Equal variances assumed 2.362 0.125 -0.781 1454 0.435 -0.036 0.046 -0.125 0.054










STIMA6 Equal variances assumed 1.113 0.292 0.331 1454 0.741 0.027 0.083 -0.135 0.190




COIMA1 Equal variances assumed 0.917 0.338 0.581 1454 0.561 0.026 0.045 -0.062 0.114


COIMA2 Equal variances assumed 0.000 0.989 -0.031 1454 0.976 -0.001 0.045 -0.089 0.086


COIMA3 Equal variances assumed 0.018 0.894 0.178 1454 0.859 0.008 0.046 -0.082 0.099


373

CSR1 Equal variances assumed 0.082 0.774 -0.388 1454 0.698 -0.018 0.046 -0.108 0.072












TRUST1 Equal variances assumed 0.082 0.774 0.764 1454 0.445 0.036 0.047 -0.056 0.127


TRUST2 Equal variances assumed 1.366 0.243 -0.537 1454 0.591 -0.023 0.043 -0.109 0.062






HABIT1 Equal variances assumed 0.177 0.674 0.435 1454 0.664 0.022 0.051 -0.077 0.121






STAC1 Equal variances assumed 5.340 0.021 3.069 1454 0.002 0.155 0.051 0.056 0.254


STAC2 Equal variances assumed 0.013 0.910 1.231 1454 0.218 0.060 0.049 -0.036 0.157


STAC3 Equal variances assumed 0.367 0.545 1.372 1454 0.170 0.067 0.049 -0.029 0.164


ALA1 Equal variances assumed 0.371 0.543 1.626 1454 0.104 0.087 0.053 -0.018 0.191








SWC1 Equal variances assumed 0.107 0.743 -1.376 1454 0.169 -0.076 0.055 -0.183 0.032




SWC3 Equal variances assumed 1.434 0.231 0.281 1454 0.779 0.015 0.054 -0.090 0.121








LPRO1 Equal variances assumed 0.022 0.881 0.348 1454 0.728 0.018 0.051 -0.083 0.118






374

LPRO4 Equal variances assumed 0.704 0.402 -0.275 1454 0.783 -0.014 0.050 -0.112 0.084






PROE1 Equal variances assumed 0.038 0.845 -0.781 1454 0.435 -0.036 0.046 -0.125 0.054


PROE2 Equal variances assumed 0.072 0.788 0.059 1454 0.953 0.003 0.047 -0.089 0.094


PROE3 Equal variances assumed 0.128 0.720 -0.847 1454 0.397 -0.040 0.047 -0.132 0.052


Appendix 5.4 - Full pie-charts summarises all respondents’ demographic information

24.96%

16.75%

23.31% 17.75%

17.23% Hanoi

Da Nang

Ho Chi Minh

Binh Duong

Can Tho

LOCATION 30.52%

68.73%

0.76%

Male

Female

Other

GENDER

0.86%

41.54%

21.15% 10.40%

8.89%

17.16% AGE RANGE Under 18

18-22

23-30

31-40

41-55

Above 55

8.07%

85.03%

6.90%

EDUCATION LEVEL

Under highschool

Under college

College,undergraduate

30.28%

7.45%

24.51%

27.91%

0.65% 9.20%

OCCUPATION Students

Self employment

Office staffs

Housewife

Unemployment

Other

375

Appendix 5.5 – The shopping behaviours of Vietnamese supermarket consumers 1. Overall, where do you prefer to go for grocery shopping?

Frequency Percent

Supermarkets 1420 48.75

Traditional markets 1386 47.58

Others 107 3.67

Total 2913 100.00

2. How often do you go to traditional markets?

Frequency Percent

Once a day 821 28.18

Twice a week 617 21.18

Three times a week 463 15.89

Once a month 339 11.64

Twice a month 256 8.79

Others 417 14.32

Total 2913 100.00

3. How often do you go to supermarkets?

Frequency Percent

Once a day 164 5.63

Twice a week 612 21.01

Three times a week 216 7.42

Once a month 764 26.23

Twice a month 732 25.13

Others 425 14.59

Total 2913 100.00

43.77%

29.28%

23.55%

2.23% 1.17% INCOME

Lower than 5 milion VND (170 GBP)

From 5 to 10 million VND (170-340GBP)

From 10 to 20 million VND (340-650GBP)

From 20 to 50 million VND (650-1620 GBP)

Higher than 50 million (above 1620 GBP)

55.58% 34.64%

8.10% 1.68% FAMILY'S EXPENDITURE FOR MONTHLY GROCERIES

Lower than 5 million VND (170 GBP)

From 5 to 10 million VND (170-5XX GBP)

From 10 to 20 million VND (5XX - 650GBP)

More than 20 million (650GBP)

376

4. Which supermarket do you usually go? (Please just choose one option)

Frequency Percent

Coopmart or BigC 1585 54.41

Lotte Mart 398 13.66

Vinmart 528 18.13

AEON 268 9.20

Others 134 4.60

Total 2913 100.00

5. Do you have any loyalty cards from the supermarket which you have just chosen at Question 4?

Frequency Percent

Yes 1656 56.85

No 1257 0.43

Total 2913 100.00

6. How long have you used it?

Frequency Percent

I have no loyalty card 1242 42.64

Less than 1 year 653 22.42

1-3 years 665 22.83

More than 3 years 353 12.12

Total 2913 100.00

7. Do you think that you are loyal to the above chosen supermarket (question 4)?

Frequency Percent

Yes 1805 61.96

No 1108 38.04

Total 2913 100.00

8. How satisfied are you with the above chosen supermarket on a scale of 1 to 5? (1 means “very

dissatisfied”, 5 means “very satisfied”)

Frequency Percent

1 26 0.89

2 94 3.23

3 936 32.13

4 1495 51.32

5 362 12.43

Total 2913 100.00

9. How satisfied are you with the offered service quality by this supermarket on a scale of 1 to 5? (1

means “very dissatisfied”, 5 means “very satisfied”)

Frequency Percent

1 19 0.65

2 131 4.50

3 948 32.54

4 1450 49.78

5 365 12.53

Total 2913 100.00

10. Do you think your favorite supermarkets meet your needs?

Frequency Percent

Yes 1004 34.47

No 380 13.04

Partly 1529 52.49

Total 2913 100.00

11. If you are not satisfied with the service or the quality of the products at a supermarket, will you back

to visit and shop there again?

Frequency Percent

Yes 1541 52.90

No 1365 46.86

Total 2913 100.00

377

12. Will you still stay with your favorite supermarket if you see an alternative attractiveness from other

supermarkets?

Frequency Percent

Yes 1468 50.39

No 1445 49.61

Total 2913 100.00

13. “I choose this supermarket’s brand name because its good store image”. Do you agree with the above

statement?

Frequency Percent

Yes 1699 58.32

No 1214 41.68

Total 2913 100.00

14. Do you think loyalty programs such as bonus points, discounts and gifts will affect your decision?

Frequency Percent

Yes 2216 76.07

No 697 23.93

Total 2913 100.00

15. If other supermarkets offer appeal promotions or discounts, would you be ready to switch to them?

Frequency Percent

Yes 2156 74.01

No 757 25.99

Total 2913 100.00

16. How many loyalty cards do you have for grocery shopping from different supermarkets?

Frequency Percent

0 1056 36.25

1 777 26.67

2 655 22.49

3 322 11.05

More than 4 103 3.54

Total 2913 100.00

17. Suppose you are always loyal to specific supermarket A, if supermarket B opens a store near you or

easier for you to get there and suppose that other factors meet your requirements, do you wish to switch

to shop at supermarket B?

Frequency Percent

Yes 2483 85.24

No 430 14.76

Total 2913 100.00

18. Does the supermarket’s brand name affect your choices?

Frequency Percent

Yes 2102 72.16

No 811 27.84

Total 2913 100.00

19. Suppose that there are two different supermarkets that you feel satisfied, all other factors are the

same, one of these is a domestic brand name, another is foreign brand name, which one will you choose?

Frequency Percent

Domestic brand name 1766 60.62

Foreign brand name 1147 39.38

Total 2913 100.00

20. Are you in charge with buying grocery products for the whole family or for yourself?

Frequency Percent

The whole family 1390 47.72

Myself 1264 43.39

I am not in charge with buying grocery

products 259 8.89

Total 2913 100.00

378

Appendix 5.6 – Internal consistency of all researched constructed before EFA

1. Internal consistency of customer perceived value (CPV)

Note: **. Correlation is significant at the 0.01 level (2-tailed).

Items Mean Std. Deviation

Inter-item correlations Corrected

Item-Total

Correlation

Cronbach's

alpha

Cronbach's

Alpha if

Item

Deleted CPV1 CPV2 CPV3 CPV4 CPV5 CPV6

CPV1 3.57 0.887 1 0.525

0.831

0.819

CPV2 3.74 0.914 .508** 1 0.65 0.794

CPV3 3.71 0.87 .477** .599** 1 0.667 0.791

CPV4 3.8 0.854 .380** .529** .543** 1 0.666 0.791

CPV5 3.69 0.89 .335** .446** .470** .579** 1 0.617 0.801

CPV6 3.44 0.909 .302** .332** .374** .427** .476** 1 0.497 0.825

2. Internal consistency of customer satisfaction (CS)

Items Mean Std.

Deviation


Item-Total

Correlation

Cronbach's

alpha

Cronbach's

Alpha if Item

Deleted

CS1 CS2 CS3 CS4 CS5

CS1 3.08 0.889 1 0.594

0.659

0.527

CS2 3.42 0.847 .616** 1 0.592 0.534

CS3 3.53 0.844 .542** .649** 1 0.567 0.545

CS4 3.45 0.901 .447** .505** .526** 1 0.529 0.556

CS5 2.28 1.268 .093** -0.03 -0.04 .068** 1 0.032 0.827

3. Internal consistency of customer loyalty (CL)

Items Mean Std.

Deviation


Item-Total

Correlation

Cronbach's

alpha

Cronbach's

Alpha if Item

Deleted CL1 CL2 CL3 CL4 CL5

CL1 3.46 0.95 1 0.587

0.821

0.794

CL2 2.88 1.063 .403** 1 0.517 0.817

CL3 3.38 0.915 .485** .442** 1 0.65 0.777

CL4 3.53 0.949 .498** .381** .588** 1 0.675 0.769

CL5 3.39 0.995 .470** .437** .507** .623** 1 0.656 0.773

379

4. Internal consistency of in-store logistics (ISL)

5. Internal consistency of service quality (SQ)

Items Mean Std.

Deviation


Item-Total

Correlation

Cronbach's

alpha

Cronbach's

Alpha if

Item

Deleted SQ1 SQ2 SQ3 SQ4 SQ5 SQ6

SQ1 3.34 0.930 1 0.678

.876

0.855

SQ2 3.45 0.879 .679** 1 0.712 0.849

SQ3 3.63 0.848 .532** .632** 1 0.667 0.857

SQ4 3.45 0.919 .533** .541** .522** 1 0.676 0.855

SQ5 3.69 0.908 .486** .479** .511** .553** 1 0.683 0.854

SQ6 3.75 0.909 .473** .485** .466** .540** .685** 1 0.665 0.857

6. Internal consistency of e-service quality (ESQ)

Items Mean Std.

Deviation


Item-Total

Correlation

Cronbach's

alpha

Cronbach's

Alpha if

Item

Deleted ISL1 ISL2 ISL3 ISL4 ISL5 ISL6 ISL7

ISL1 3.59 1.021 1 0.598

.855

0.838

ISL2 3.74 0.953 .553** 1 0.627 0.833

ISL3 3.94 0.948 .507** .519** 1 0.645 0.831

ISL4 3.97 0.935 .382** .442** .560** 1 0.623 0.834

ISL5 3.89 0.908 .408** .428** .464** .529** 1 0.631 0.833

ISL6 3.76 0.986 .415** .406** .395** .430** .513** 1 0.606 0.836

ISL7 3.88 0.929 .398** .425** .405** .431** .456** .547** 1 0.597 0.837

Items Mea

n

Std.

Deviatio

n


Item-Total

Correlatio

n

Cronbac

h's alpha

Cronba

ch's

Alpha if

Item

Deleted

ESQ

1

ESQ

2

ESQ

3

ESQ

4

ESQ

5

ESQ

6

ESQ

7

ESQ

8

ESQ

9

ESQ1

0

ESQ1 3.19 0.993 1 0.633

.908

0.901

ESQ2 3.26 1.021 .634** 1 0.650 0.900

ESQ3 3.42 0.952 .552** .556** 1 0.680 0.898

ESQ4 3.51 0.950 .452** .484** .548** 1 0.657 0.900

ESQ5 3.58 0.937 .436** .476** .521** .575** 1 0.660 0.900

ESQ6 3.63 0.952 .433** .527** .508** .526** .594** 1 0.653 0.900

ESQ7 3.30 1.002 .457** .407** .452** .438** .455** .419** 1 0.672 0.899

ESQ8 3.36 0.937 .441** .439** .472** .473** .461** .456** .733** 1 0.720 0.896

ESQ9 3.44 0.938 .444** .429** .483** .453** .469** .461** .607** .682** 1 0.704 0.897

ESQ10 3.50 0.954 .395** .406** .451** .466** .443** .462** .541** .633** .670** 1 0.665 0.899

380

7. Internal consistency of product quality (PROQ)

Items Mean Std.

Deviation


Item-Total

Correlation

Cronbach's

alpha

Cronbach's

Alpha if

Item

Deleted PROQ1 PROQ2 PROQ3 PROQ4

PROQ1 3.88 0.910 1 0.599

.824

0.802

PROQ2 3.87 0.855 .650** 1 0.727 0.743

PROQ3 3.60 0.868 .468** .598** 1 0.672 0.768

PROQ4 3.64 0.871 .405** .522** .605** 1 0.602 0.799

8. Internal consistency of price (PRICE)

Items Mean Std.

Deviation


Item-Total

Correlation

Cronbach's

alpha

Cronbach's

Alpha if

Item

Deleted PRICE1 PRICE2 PRICE3

PRICE1 3.65 0.906 1 0.651

.807

0.740

PRICE2 3.44 1.037 .572** 1 0.653 0.744

PRICE3 3.57 0.899 .592** .593** 1 0.668 0.724

9. Internal consistency of customer service (CUSER)

Items Mean

Std.

Deviatio

n

Inter-item correlations Correct

ed Item-

Total

Correla

tion

Cronb

ach's

alpha

Cronbach's

Alpha if

Item

Deleted

CUSE

R1 2 3 4 5 6 7 8 9 10

CUSER1 3.05 1.076 1 0.571

.884

0.876

CUSER2 3.48 1.060 .450** 1 0.622 0.872

CUSER3 3.31 1.014 .664** .555** 1 0.679 0.868

CUSER4 3.36 0.970 .478** .463** .574** 1 0.630 0.872

CUSER5 3.79 0.986 .280** .443** .383** .420** 1 0.539 0.878

CUSER6 3.61 1.042 .274** .413** .351** .403** .504** 1 0.591 0.875

CUSER7 3.58 0.980 .406** .412** .451** .412** .414** .578** 1 0.642 0.871

CUSER8 3.45 1.044 .361** .400** .426** .417** .359** .466** .519** 1 0.643 0.871

CUSER9 3.41 1.008 .338** .411** .417** .396** .326** .400** .434** .581** 1 0.617 0.873

CUSER10 3.48 1.008 .397** .391** .437** .422** .326** .387** .422** .536** .607** 1 0.619 0.873

381

10. Internal consistency of customer experience (CUEXP)

Items Mean Std.

Deviation


Item-Total

Correlation

Cronbach's

alpha

Cronbach's

Alpha if

Item

Deleted CUEXP1 CUEXP2 CUEXP3 CUEXP4

CUEXP1 3.59 0.894 1 0.691

.848

0.805

CUEXP2 3.63 0.910 .643** 1 0.727 0.789

CUEXP3 3.70 0.871 .645** .666** 1 0.742 0.784

CUEXP4 3.70 0.940 .476** .526** .552** 1 0.591 0.848

11. Internal consistency of retail brand experience (RBEX)

Items Mean Std. Deviation Inter-item correlations Corrected

Item-Total

Correlation

Cronbach's

alpha

Cronbach's

Alpha if Item

Deleted RBEX1 RBEX2 RBEX3 RBEX4 RBEX5 RBEX6

RBEX1 3.48 0.956 1 0.63

0.834

0.803

RBEX2 3.59 0.894 .594** 1 0.662 0.797

RBEX3 3.37 1.001 .474** .510** 1 0.626 0.804

RBEX4 3.59 0.909 .465** .532** .540** 1 0.657 0.798

RBEX5 3.58 0.901 .500** .502** .529** .576** 1 0.662 0.797

RBEX6 3.06 1.042 .348** .339** .318** .351** .371** 1 0.439 0.844

12. Internal consistency of store image (STIMA)

Items Mean

Std.

Devia

tion


Item-Total

Correlation

Cronbach'

s alpha

Cronbach's

Alpha if Item

Deleted STIMA1 2 3 4 5 6 7

STIMA1 3.54 0.889 1 0.628

.848

0.825

STIMA2 3.47 0.926 .614** 1 0.641 0.823

STIMA3 3.55 0.879 .561** .561** 1 0.692 0.816

STIMA4 3.67 0.891 .471** .519** .564** 1 0.643 0.823

STIMA5 3.56 0.904 .428** .436** .475** .498** 1 0.623 0.825

STIMA6 3.60 1.281 .304** .335** .395** .361** .391** 1 0.477 0.860

STIMA7 3.71 0.875 .471** .428** .520** .477** .568** .412** 1 0.645 0.823

13. Internal consistency of corporate image (COIMA)

Items Mean Std.

Deviation


Item-Total

Correlation

Cronbach's

alpha

Cronbach's

Alpha if

Item

Deleted COIMA1 COIMA2 COIMA3

COIMA1 3.74 0.870 1 0.714

0.831

0.742

COIMA2 3.81 0.865 .720** 1 0.741 0.714

COIMA3 3.65 0.893 .555** .590** 1 0.617 0.837

382

14. Internal consistency of corporate social responsibility (CSR)

Items Mean Std.

Deviation


Item-Total

Correlation

Cronbach's

alpha

Cronbach's

Alpha if

Item

Deleted CSR1 CSR2 CSR3 CSR4 CSR5 CSR6

CSR1 3.55 0.879 1 0.691

.886

0.867

CSR2 3.48 0.898 .611** 1 0.662 0.872

CSR3 3.63 0.863 .594** .595** 1 0.741 0.859

CSR4 3.65 0.864 .539** .535** .647** 1 0.724 0.862

CSR5 3.70 0.852 .558** .485** .597** .626** 1 0.720 0.863

CSR6 3.71 0.893 .492** .467** .534** .564** .629** 1 0.659 0.873

15. Internal consistency of trust (TRUST)

Items Mean Std.

Deviation


Item-Total

Correlation

Cronbach's

alpha

Cronbach's

Alpha if

Item

Deleted TRUST1 TRUST2 TRUST3 TRUST4

TRUST1 3.61 0.902 1 0.766

.866

0.808

TRUST2 3.71 0.851 .758** 1 0.782 0.803

TRUST3 3.69 0.877 .642** .709** 1 0.725 0.825

TRUST4 3.62 0.907 .559** .523** .527** 1 0.599 0.876

16. Internal consistency of habit (HABIT)

Items Mean Std.

Deviation


Item-Total

Correlation

Cronbach's

alpha

Cronbach's

Alpha if

Item

Deleted HABIT1 HABIT2 HABIT3

HABIT1 3.71 0.953 1 0.640

.820

0.785

HABIT2 3.65 0.937 .604** 1 0.708 0.716

HABIT3 3.67 0.925 .558** .647** 1 0.672 0.753

17. Internal consistency of store accessibility (STAC)

Items Mean Std.

Deviation


Item-Total

Correlation

Cronbach's

alpha

Cronbach's

Alpha if

Item

Deleted STAC1 STAC2 STAC3

STAC1 3.76 1.356 1 0.590

.813

0.889

STAC2 3.82 0.940 .569** 1 0.751 0.680

STAC3 3.84 0.940 .550** .801** 1 0.734 0.695

383

18. Internal consistency of alternative attractiveness (ALA)

Items Mean Std.

Deviation


Item-Total

Correlation

Cronbach's

alpha

Cronbach's

Alpha if

Item

Deleted ALA1 ALA2 ALA3 ALA4

ALA1 3.14 1.021 1 0.695

.866

0.838

ALA2 3.38 0.965 .619** 1 0.701 0.836

ALA3 3.19 1.026 .592** .597** 1 0.729 0.824

ALA4 3.29 1.006 .604** .609** .692** 1 0.741 0.819

19. Internal consistency of switching costs (SWC)

Items Mean Std.

Deviation


Item-Total

Correlation

Cronbach's

alpha

Cronbach's

Alpha if Item

Deleted SWC1 SWC2 SWC3 SWC4 SWC5 SWC6

SWC1 3.04 1.063 1 0.640

.879

0.865

SWC2 2.95 1.102 .680** 1 0.724 0.851

SWC3 3.17 1.040 .526** .617** 1 0.710 0.854

SWC4 3.24 1.062 .472** .548** .614** 1 0.709 0.854

SWC5 3.21 1.078 .461** .531** .558** .629** 1 0.694 0.856

SWC6 3.33 1.054 .434** .489** .501** .552** .589** 1 0.636 0.866

20. Internal consistency of loyalty programs (LPRO)

Items Mean Std.

Deviation


Item-Total

Correlation

Cronbach's

alpha

Cronbach's

Alpha if

Item Deleted LPRO1 LPRO2 LPRO3 LPRO4 LPRO5 LPRO6

LPRO1 3.59 0.982 1 0.668

.888

0.874

LPRO2 3.73 0.938 .671** 1 0.723 0.866

LPRO3 3.72 0.941 .604** .709** 1 0.741 0.863

LPRO4 3.65 0.941 .561** .626** .677** 1 0.768 0.859

LPRO5 3.53 0.986 .502** .488** .549** .620** 1 0.706 0.868

LPRO6 3.44 1.061 .411** .443** .461** .593** .690** 1 0.631 0.882

21. Internal consistency of promotion effects (PROE)

Items Mean Std.

Deviation


Item-Total

Correlation

Cronbach's

alpha

Cronbach's

Alpha if

Item

Deleted PROE1 PROE2 PROE3

PROE1 3.65 0.874 1 0.661

.847

0.836

PROE2 3.79 0.896 .639** 1 0.762 0.738

PROE3 3.81 0.894 .585** .717** 1 0.720 0.780

384

Appendix 5.7- KMO and Barlett’s Test- Communalities (EFA)

KMO and Bartlett's Test

Kaiser-Meyer-Olkin Measure of

Sampling Adequacy. 0.966

Bartlett's

Test of

Sphericity

Approx. Chi-

Square 105721.538

df 1953

Sig. 0

Communalities

Initial Extraction

CPV2 0.497 0.623

CPV3 0.467 0.602

CPV4 0.431 0.495

CS1 0.479 0.566

CS2 0.572 0.709

CS3 0.535 0.595

CL3 0.438 0.493

CL4 0.544 0.735

CL5 0.491 0.556

ISL1 0.480 0.574

ISL2 0.437 0.575

ISL3 0.415 0.494

SQ4 0.468 0.497

SQ5 0.565 0.704

SQ6 0.569 0.682

ESQ4 0.444 0.526

ESQ5 0.518 0.643

ESQ6 0.493 0.565

ESQ7 0.613 0.684

ESQ8 0.650 0.826

ESQ9 0.543 0.588

PROQ1 0.527 0.559

PROQ2 0.591 0.809

PROQ3 0.479 0.500

PRICE1 0.548 0.623

PRICE2 0.487 0.649

PRICE3 0.556 0.608

CUSER1 0.496 0.645

CUSER3 0.550 0.706

CUEXP1 0.585 0.651

CUEXP2 0.567 0.677

CUEXP3 0.579 0.658

RBEX1 0.506 0.552

RBEX2 0.515 0.579

RBEX4 0.509 0.565

RBEX5 0.489 0.536

STIMA1 0.597 0.663

STIMA2 0.504 0.609

STIMA3 0.481 0.539

CSR3 0.549 0.624

CSR4 0.563 0.659

CSR5 0.520 0.592

TRUST1 0.684 0.765

TRUST2 0.688 0.788

TRUST3 0.603 0.646

HABIT1 0.523 0.574

HABIT2 0.532 0.706

HABIT3 0.534 0.612

STAC1 0.667 0.730

STAC2 0.728 0.827

STAC3 0.701 0.779

ALA2 0.459 0.534

ALA3 0.561 0.694

ALA4 0.563 0.705

SWC2 0.506 0.604

SWC3 0.514 0.681

SWC4 0.457 0.546

LPRO2 0.576 0.661

LPRO3 0.615 0.769

LPRO4 0.558 0.623

PROE1 0.540 0.578

PROE2 0.616 0.782

PROE3 0.578 0.663

Extraction Method: Principal

Axis Factoring.

385

Appendix 5.8 - Total Variance Explained (EFA)

Total Variance Explained

Factor

Initial Eigenvalues Extraction Sums of Squared Loadings

Rotation Sums of Squared

Loadingsa

Total % of

Variance Cumulative

% Total

% of Variance

Cumulative %

Total

1 21.243 33.718 33.718 20.881 33.145 33.145 9.209

2 3.098 4.918 38.636 2.733 4.339 37.484 10.622

3 2.422 3.845 42.481 2.111 3.351 40.834 10.098

4 1.931 3.065 45.546 1.575 2.500 43.334 10.424

5 1.735 2.754 48.300 1.427 2.266 45.600 5.398

6 1.663 2.639 50.939 1.285 2.040 47.639 10.500

7 1.485 2.357 53.296 1.132 1.797 49.436 3.374

8 1.352 2.146 55.442 1.003 1.593 51.029 11.408

9 1.292 2.051 57.493 0.920 1.460 52.489 10.644

10 1.287 1.916 59.410 0.867 1.376 53.865 11.436

11 1.273 1.782 61.191 0.760 1.206 55.071 12.226

12 1.265 1.720 62.911 0.713 1.132 56.203 11.375

13 1.247 1.578 64.489 0.678 1.076 57.279 14.268

14 1.235 1.554 66.043 0.634 1.007 58.287 13.655

15 1.189 1.548 67.591 0.607 0.964 59.251 14.068

16 1.176 1.452 69.044 0.552 0.876 60.127 12.544

17 1.135 1.342 70.385 0.495 0.785 60.912 14.347

18 1.102 1.316 71.701 0.456 0.724 61.636 12.698

19 1.094 1.294 72.995 0.433 0.687 62.323 13.459

20 1.047 1.263 74.259 0.417 0.662 62.985 9.087

21 1.022 1.094 75.353 0.325 0.515 63.500 13.718

22 0.921 0.986 76.339

23 0.871 0.906 77.245

24 0.743 0.861 78.106

25 0.620 0.826 78.932

26 0.504 0.800 79.731

27 0.490 0.778 80.510

28 0.484 0.769 81.279

29 0.468 0.744 82.022

30 0.465 0.738 82.760

31 0.454 0.720 83.480

32 0.447 0.709 84.189

33 0.441 0.700 84.889

34 0.417 0.662 85.552

35 0.409 0.650 86.202

36 0.402 0.638 86.839

37 0.393 0.623 87.462

38 0.384 0.609 88.072

39 0.377 0.598 88.670

40 0.374 0.594 89.264

41 0.370 0.587 89.851

42 0.364 0.577 90.429

43 0.357 0.567 90.995

44 0.347 0.552 91.547

386

45 0.338 0.536 92.083

46 0.332 0.527 92.610

47 0.330 0.523 93.133

48 0.323 0.512 93.646

49 0.317 0.503 94.149

50 0.309 0.490 94.639

51 0.303 0.480 95.119

52 0.298 0.473 95.593

53 0.294 0.466 96.059

54 0.289 0.459 96.518

55 0.284 0.451 96.969

56 0.276 0.438 97.407

57 0.270 0.429 97.836

58 0.267 0.424 98.260

59 0.253 0.402 98.663

60 0.231 0.367 99.029

61 0.228 0.362 99.392

62 0.201 0.318 99.710

63 0.183 0.290 100.000

Extraction Method: Principal Axis Factoring.

a. When factors are correlated, sums of squared loadings cannot be added to obtain a total variance.

387

Appendix 5.9 - Pattern matrix (EFA)

Pattern matrix

Cronbach's alpha

Factor

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21

STAC ESQX1 LPRO CPV SWC ISL ALA CL PROE HABIT SQ PRICE CUEXP TRUST RBEX CS CSR ESQX2 PROQ CUSER STIMA

0.911 0.86 0.859 0.79 0.813 0.769 0.838 0.8 0.847 0.82 0.813 0.807 0.847 0.876 0.817 0.819 0.832 0.796 0.799 0.797 0.805

STAC2 0.914

STAC3 0.884

STAC1 0.841

ESQ8 0.961

ESQ7 0.771

ESQ9 0.647

LPRO3 0.919

LPRO2 0.797

LPRO4 0.728

CPV3 0.813

CPV2 0.785

CPV4 0.629

SWC3 0.871

SWC4 0.743

SWC2 0.708

ISL2 0.804

ISL1 0.659

ISL3 0.646

ALA4 0.831

ALA3 0.826

ALA2 0.724

CL4 0.922

CL5 0.685

CL3 0.635

PROE2 0.918

PROE3 0.805

PROE1 0.565

HABIT2 0.914

388

HABIT3 0.732

HABIT1 0.605

SQ5 0.873

SQ6 0.805

SQ4 0.537

PRICE2 0.894

PRICE1 0.687

PRICE3 0.605

CUEXP2 0.861

CUEXP3 0.783

CUEXP1 0.713

TRUST2 0.911

TRUST1 0.816

TRUST3 0.69

RBEX2 0.735

RBEX4 0.651

RBEX5 0.632

RBEX1 0.625

CS2 0.874

CS1 0.773

CS3 0.657

CSR4 0.817

CSR3 0.738

CSR5 0.736

ESQ5 0.832

ESQ4 0.709

ESQ6 0.665

PROQ2 1.016

PROQ1 0.601

PROQ3 0.556

CUSER1 0.807

CUSER3 0.781

STIMA2 0.812

STIMA1 0.643

STIMA3 0.59

389

Extraction Method: Principal Axis Factoring.

Rotation Method: Promax with Kaiser Normalization.

a. Rotation converged in 9 iterations.

390

Appendix 5.10 – All measurement variables remained after EFA

Factors and its variables

Customer perceived value (CPV)

CPV2 Prices are fair


CPV4 Compared to the price we pay, we get reasonable quality

Customer satisfaction (CS)

CS1 Complete service offered by a supermarket is significantly above expected

CS2 In general, my satisfaction level related to the supermarket that I have already dealt with is high


the supermarket

Customer loyalty (CS)

CL3 I will say positive things about the retailers and recommend it to others

CL4 I would consider the supermarket my first choice to do shopping

CL5 I will always continue to choose the products of this grocery store instead others

In-store logistics (ISL)




Service quality (SQ)

SQ4 Service employees at this store have good product knowledge

SQ5 Service employees at this store are willing to help customers


E-service quality 1 (ESQX2)




E-service quality (ESQX1)




Product quality (PROQ)


PROQ2 Products in this store are of consistent quality


391

Price

PRICE1 Goods at this store are reasonably priced

PRICE2 The prices of the products in this supermarket are cheaper than others

PRICE3 Goods at this store offer value for money

Customer service



Customer experience




Retail brand experience





Store image




Corporate social responsibility




Trust


TRUST2 I consider that to shop in the stores of this retailer is a guarantee


Habit


HABIT2 I have no need to think about doing (shopping at this supermarket)


ways)

Store accessibility

STAC1 I can get to store X quickly

STAC2 I can get to store X without problems


392

Alternative attractiveness


ALA3 I need to change the place for shopping, there are other good department stores to choose from


Switching costs


SWC3 Search and evaluate the untested service department store costs you time and effort


Loyalty programs

LPRO2 Collecting points is entertaining



Promotion effects

PROE1 I find the promotional activities of this online supermarket to be very persuasive and positive

PROE2 My purchasing willingness arises from the promotional activities


393

Appendix 6.1 - Results from CFA_2ndrun

394

Appendix 6.2 - The final CFAmodel_Results from CFA_4th

run_after construct validity

checking

395

Appendix 6.3 - Common method bias testing

396

Appendix 6.4 - The initial SEM (SEM_1strun) and its results

Model Fit Summary

CMIN

Model NPAR CMIN DF P CMIN/DF

Default model 332 176.828 19 0 9.307

Saturated model 351 0 0

Independence model 26 60829.115 325 0 187.167

RMR, GFI

Model RMR GFI AGFI PGFI

Default model 0.002 0.995 0.915 0.054

Saturated model 0 1

Independence model 0.21 0.152 0.085 0.141

Baseline Comparisons

Model NFI RFI IFI TLI

CFI Delta1 rho1 Delta2 rho2

Default model 0.997 0.95 0.997 0.955 0.997


Independence model 0 0 0 0 0

Parsimony-Adjusted Measures

Model PRATIO PNFI PCFI

Default model 0.058 0.058 0.058


Independence model 1 0 0

NCP

Model NCP LO 90 HI 90

397

Default model 157.828 118.947 204.18


Independence model 60504.115 59696.987 61317.53

FMIN

Model FMIN F0 LO 90 HI 90

Default model 0.061 0.054 0.041 0.07

Saturated model 0 0 0 0


RMSEA

Model RMSEA LO 90 HI 90 PCLOSE

Default model 0.053 0.046 0.061 0.207

Independence model 0.253 0.251 0.255 0

AIC Model AIC BCC BIC CAIC

Default model 840.828 847.043 2825.172 3157.172

Saturated model 702 708.57 2799.906 3150.906


ECVI

Model ECVI LO 90 HI 90 MECVI

Default model 0.289 0.275 0.305 0.291

Saturated model 0.241 0.241 0.241 0.243


HOELTER

Model

HOELTER HOELTER

0.05 0.01

Default model 497 596

Independence model 18 19

Appendix 6.5 - SEM_2rdrun_Final

Model Fit Summary

CMIN

Model NPAR CMIN DF P CMIN/DF

Default model 249 159.718 27 0 5.915


Independence model 23 55899.123 253 0 220.945

RMR, GFI

Model RMR GFI AGFI PGFI

Default model 0.003 0.995 0.952 0.097

Saturated model 0 1


Baseline Comparisons

Model

NFI RFI IFI TLI CFI

Delta1 rho1 Delta2 rho2

Default model 0.997 0.973 0.998 0.978 0.998


398

Independence model 0 0 0 0 0

Parsimony-Adjusted Measures

Model PRATIO PNFI PCFI

Default model 0.107 0.106 0.106


Independence model 1 0 0

NCP

Model NCP LO 90 HI 90

Default model 132.718 96.628 176.318


Independence model 55646.123 54872.365 56426.167

FMIN

Model FMIN F0 LO 90 HI 90

Default model 0.055 0.046 0.033 0.061

Saturated model 0 0 0 0


RMSEA

Model RMSEA LO 90 HI 90 PCLOSE

Default model 0.041 0.035 0.047 0.991

Independence model 0.275 0.273 0.277 0

AIC

Model AIC BCC BIC CAIC

Default model 657.718 661.857 2145.976 2394.976

Saturated model 552 556.587 2201.635 2477.635


ECVI

Model ECVI LO 90 HI 90 MECVI

Default model 0.226 0.213 0.241 0.227

Saturated model 0.19 0.19 0.19 0.191


HOELTER

Model

HOELTER HOELTER

0.05 0.01

Default model 732 857

Independence model 16 17

399

Appendix 6.6 - Summarising all hypothesis testing results

CUSTOMER PERCEIVED VALUE

H20A Good price offered positively affects customer perceived value PRICE 0.295 Supported

H13A In-store logistics have a strong and positive effect on customer perceived value ISL 0.199 Supported

H25 Trust positively affects customer perceived value TRUST 0.161 Supported

H19A Promotion effects positively affect customer perceived value PROE 0.124 Supported

H17B E-service quality X2 (E-S-QUAL) has a significant positive effect on customer perceived value ESQX2 0.114 Supported

H9A Switching costs have a negative effect on customer perceived value SWC -0.081 Supported

H12A There is a positive relationship between service quality and customer perceived value SQ 0.061 Supported

H16 The higher customer service, the better customer perceived value CUSER 0.057 Supported

H5A People who choose different supermarkets for shopping have different customer perceived value Q4 -0.041 Supported

H21A Good product quality is positively associated with customer perceived value PROQ Not supported

H22A Cooperate social responsibility is directly and positively associated with customer perceived value CSR Not supported

H1A Income has a positive effect on customer perceived value INCOME Not supported

H2A Location where people stay has a positive effect on customer perceived value LOCATION Not supported

H3A Age positively affects customer perceived value AGE Not supported

H4A Gender positively affects customer perceived value GENDER Not supported

H17A E-service quality about X1 (W-S-QUAL) has a significant positive effect on customer perceived

value ESQX1

Significant but not

supported

CUSTOMER SATISFACTION

H7A Customer perceived value has a positive influence on customer satisfaction CPV 0.301 Supported

H13B In-store logistics have a strong and positive effect on customer satisfaction ISL 0.239 Supported

H12B There is a positive relationship between service quality and customer satisfaction SQ 0.214 Supported

H14 Store image is positively associated with customer satisfaction STIMA 0.188 Supported

H6 Customer experience has a positive effect on customer satisfaction CUEX 0.148 Supported

H21B Good product quality is positively associated with customer satisfaction PROQ -0.144 Supported

H10A High-perceived alternative attractiveness has a negative influence on customer satisfaction ALA -0.113 Supported

H9B Switching costs have a positive effect on customer satisfaction SWC 0.071 Supported

H20B Good price offered positively affects customer satisfaction PRICE 0.051 Supported

H1B Income has a positive effect on customer satisfaction INCOME 0.025 Supported

H2B Location where people stay has a positive effect on customer satisfaction LOCATION 0.024 Supported

H11A Customer satisfaction is positively affected by retail brand experience RBEX Not supported

H3B Age positively affects customer satisfaction AGE Not supported

H4B Gender positively affects customer satisfaction GENDER Not supported

H5B People who choose different supermarkets for shopping have different behavior on customer

satisfaction Q4 Not supported

CUSTOMER LOYALTY

H11B Customer loyalty is positively affected by retail brand experience RBEX 0.306 Supported

H12C Service quality positively affects customer loyalty. SQ 0.179 Supported

H8 Customer satisfaction is directly and positively associated with customer loyalty CS 0.178 Supported

H19B Promotion has a positive effect on customer loyalty PROE 0.141 Supported

H9C High-perceived switching costs have a positive influence on customer loyalty SWC 0.113 Supported

H17D E-service quality X2 (E-S-QUAL) has a significant positive effect on customer loyalty ESQX2 0.106 Supported

H10B High-perceived alternative attractiveness has a negative influence on customer loyalty ALA -0.101 Supported

H20C Good price offered positively affects customer loyalty PRICE 0.069 Supported

H26 Habit positively affects customer loyalty HABIT 0.057 Supported

H1C Income has a positive effect on customer loyalty INCOME 0.024 Supported

H7B Customer perceived value has a direct positive impact on customer loyalty CPV Not supported

H22B Cooperate social responsibility is directly and positively associated with customer loyalty CSR Not supported

H21C Good product quality is positively associated with customer loyalty PROQ Not supported

H5C People who choose different supermarkets for shopping have different behavior on customer

loyalty Q4 Not supported

H2C Location where people stay has a positive effect on customer loyalty LOCATION Not supported

H3C Age positively affects customer loyalty AGE Not supported

H4C Gender positively affects customer loyalty GENDER Not supported

H17C E-service quality X1 (W-S-QUAL) has a significant positive effect on customer loyalty ESQX1 Significant but not supported

H15 Store accessibility positively affects customer loyalty STAC Significant but not

supported

H18 Loyalty programs have a positive effect on customer loyalty LPRO Significant but not supported

400

Appendix 7.1- Comparison across groups for factors related to customer loyalty

Supermarket business model

Path Name

Coopmart or

BigC Beta

Lotte Mart

Beta

Difference

in Betas

P-Value for


ESQX2 → CL. 0.043 0.208*** -0.165 0.014 The positive relationship between CL and ESQX2 is stronger for Lotte Mart.

RBEX → CL. 0.326*** 0.219*** 0.107 0.088 The positive relationship between CL and RBEX is stronger for Coopmart or BigC.

PRICE → CL. 0.061** 0.158*** -0.096 0.055 The positive relationship between CL and PRICE is stronger for Lotte Mart.

ALA → CL. -0.060*** -0.228*** 0.168 0.000 The negative relationship between CL and ALA is stronger for Lotte Mart.

Path Name Coopmart or

BigC Beta Vinmart Beta

Difference

in Betas

P-Value for


ESQX2 → CL. 0.043 0.159*** -0.116 0.043 The positive relationship between CL and ESQX2 is stronger for Vinmart.

ALA → CL. -0.060*** -0.172*** 0.113 0.001 The negative relationship between CL and ALA is stronger for Vinmart.


Beta Vinmart Beta

Difference

in Betas

P-Value for


PRICE → CL. 0.158*** 0.009 0.149 0.016 The positive relationship between CL and PRICE is stronger for Lotte Mart.


BigC Beta Aeon Beta

Difference

in Betas

P-Value for


ESQX2 → CL. 0.043 0.173* -0.13 0.094 The positive relationship between CL and ESQX2 is stronger for Aeon.

PROE → CL. 0.170*** 0.019 0.151 0.034 The positive relationship between CL and PROE is stronger for Coopmart or BigC.

GENDER

Path Name MALE Beta

FEMALE

Beta

Difference

in Betas

P-Value for


PROE → CL. 0.212*** 0.110*** 0.102 0.032 The positive relationship between CL and PROE is stronger for MALE.

INCOME

Path Name

Under 5

million VND

Beta

From 5-10

million VND

Beta

Difference

in Betas

P-Value for


SQ → CL. 0.131*** 0.284*** -0.154 0.011 The positive relationship between CL and SQ is stronger for From 5-10 million

VND.

PRICE → CL. 0.111*** -0.029 0.139 0.001 The positive relationship between CL and PRICE is stronger for Under 5 million

VND.

LOCATION

Path Name HCM Beta Hanoi Beta

Difference

in Betas

P-Value for


HABIT → CL. 0.108*** 0.034 0.074 0.091 The positive relationship between CL and HABIT is stronger for HCM.

ESQX2 → CL. 0.158*** 0.063 0.095 0.089 The positive relationship between CL and ESQX2 is stronger for HCM.

RBEX → CL. 0.238*** 0.352*** -0.115 0.050 The positive relationship between CL and RBEX is stronger for Hanoi.

Path Name HCM Beta Da Nang Beta Difference

in Betas

P-Value for


SQ → CL. 0.268*** 0.099 0.169 0.045 The positive relationship between CL and SQ is stronger for HCM.

AGE RANGES

Path Name 18-22 Beta 23-30 Beta

Difference

in Betas

P-Value for


SQ → CL. 0.105** 0.229*** -0.124 0.071 The positive relationship between CL and SQ is stronger for 23-30.

Path Name 18-22 Beta 41-55 Beta Difference

in Betas

P-Value for


CS → CL. 0.304*** 0.023 0.281 0.063 The positive relationship between CL and CS is stronger for 18-22.

SWC → CL. 0.090*** -0.001 0.091 0.092 The positive relationship between CL and SWC is stronger for 18-22.

401

PROE → CL. 0.112*** 0.390*** -0.278 0.001 The positive relationship between CL and PROE is stronger for 41-55.

PRICE → CL. 0.050* 0.160* -0.109 0.076 The positive relationship between CL and PRICE is stronger for 41-55.

SQ → CL. 0.105** 0.295** -0.19 0.061 The positive relationship between CL and SQ is stronger for 41-55.

Path Name 23-30 Beta above 55 Beta

Difference

in Betas

P-Value for


SWC → CL. 0.117*** 0.234*** -0.117 0.011 The positive relationship between CL and SWC is stronger for above 55.


in Betas

P-Value for


PRICE → CL. 0.084* -0.051 -0.135 0.020 The positive relationship between CL and PRICE is stronger for 23-30.

ESQX2 → CL. 0.120** -0.017 -0.137 0.089 The positive relationship between CL and ESQX2 is stronger for 23-30.

OCCUPATION

Path Name Housewife Beta

Office staffs

Beta

Difference

in Betas

P-Value for


HABIT → CL. 0.024 0.105*** -0.081 0.052 The positive relationship between CL and HABIT is stronger for Office staffs.

Path Name Students Beta

Self

employment

Beta

Difference

in Betas

P-Value for

Difference z-score

RBEX → CL. 0.332*** 0.152* 0.18 NaN -2.365**

Path Name

Self

employment

Beta

Office staffs

Beta

Difference

in Betas

P-Value for

Difference z-score

RBEX → CL. 0.152* 0.321*** -0.169 NaN 2.301**

EDUCATION LEVEL

Path Name A levels Beta

College+ U

Beta

Difference

in Betas

P-Value for


CS → CL. 0.145** 0.406** -0.262 0.097 The positive relationship between CL and CS is stronger for College+ U.

Path Name GCSE's Beta College+U

Beta

Difference

in Betas

P-Value for


ESQX1 → CL. -0.150** 0.128* -0.277 0.000 The relationship between CL and ESQX1 is negative for GCSE's and positive for

College-U.

Appendix 7.2- Comparison across groups for factors related to customer satisfaction

Supermarket business model

Path Name

Coopmart

or BigC

Beta

Lotte Mart

Beta

Difference

in Betas

P-Value for


SQ → CS. 0.224*** 0.107* 0.117 0.03 The positive relationship between CS and SQ is stronger for Coopmart or BigC.


ISL → CS. 0.208*** 0.306*** -0.098 0.079 The positive relationship between CS and ISL is stronger for Lotte Mart.

INCOME → CS. 0.011 0.084*** -0.073 0.01 The positive relationship between CS and INCOME is stronger for Lotte Mart.

Path Name

Coopmart

or BigC

Beta

Vinmart

Beta

Difference

in Betas

P-Value for


CUEXP → CS. 0.119*** 0.219*** -0.1 0.045 The positive relationship between CS and CUEXP is stronger for Vinmart.


Path Name

Coopmart

or BigC

Beta

Aeon Beta Difference

in Betas

P-Value for


ALA → CS. -0.105*** -0.173*** 0.067 0.065 The negative relationship between CS and ALA is stronger for Aeon.

SQ → CS. 0.224*** 0.323*** -0.099 0.055 The positive relationship between CS and SQ is stronger for Aeon.

PROQ → CS. 0.119*** 0.300*** 0.181 0.006 The positive relationship between CS and PROQ is stronger for Aeon.

402


Beta

Vinmart

Beta

Difference

in Betas

P-Value for


SQ → CS. 0.107* 0.220*** -0.113 0.067 The positive relationship between CS and SQ is stronger for Vinmart.

INCOME

Path Name

Under 5

million

VND Beta

From 5-10

million

VND Beta

Difference

in Betas

P-Value for


CPV → CS. 0.287*** 0.346*** -0.058 0.057 The positive relationship between CS and CPV is stronger for From 5-10 million

VND.

STIMA → CS. 0.238*** 0.121*** 0.117 0.007 The positive relationship between CS and STIMA is stronger for Under 5 million

VND.

Path Name

Under 5

million

VND Beta

From 10-20

million

VND Beta

Difference

in Betas

P-Value for


ISL → CS. 0.262*** 0.145*** 0.117 0.013 The positive relationship between CS and ISL is stronger for Under 5 million VND.

SQ → CS. 0.183*** 0.282*** -0.099 0.063 The positive relationship between CS and SQ is stronger for From 10-20 million

VND.

LOCATION

Path Name HCM Beta Hanoi Beta Difference

in Betas

P-Value for


ISL → CS. 0.172*** 0.277*** -0.105 0.053 The positive relationship between CS and ISL is stronger for Hanoi.

Path Name Can Tho

Beta

Binh Duong

Beta

Difference

in Betas

P-Value for


ALA → CS. -0.091*** -0.129*** 0.038 0.069 The negative relationship between CS and ALA is stronger for Binh Duong.

SQ → CS. 0.145*** 0.257*** -0.112 0.04 The positive relationship between CS and SQ is stronger for Binh Duong.

AGE RANGES


in Betas

P-Value for


STIMA → CS. 0.206*** 0.109** 0.097 0.069 The positive relationship between CS and STIMA is stronger for 18-22.

Path Name 23-30 Beta above 55

Beta

Difference

in Betas

P-Value for


STIMA → CS. 0.109** 0.217*** -0.108 0.067 The positive relationship between CS and STIMA is stronger for above 55.

SWC → CS. 0.059* 0.148*** -0.088 0.014 The positive relationship between CS and SWC is stronger for above 55.


in Betas

P-Value for


CPV → CS. 0.214*** 0.327*** -0.112 0.030 The positive relationship between CS and CPV is stronger for 23-30.

GENDER

Path Name MALE Beta FEMALE

Beta

Difference

in Betas

P-Value for


ALA → CS. -0.139*** -0.102*** -0.037 0.054 The negative relationship between CS and ALA is stronger for MALE.

OCCUPATION

Path Name Students

Beta

Self

employment

Beta

Difference

in Betas

P-Value for

Difference z-score

STIMA → CS. 0.231*** 0.068 0.164 NaN -2.318**

PROQ → CS. 0.157*** 0.008 -0.165 NaN 2.137**

Path Name

Self

employment

Beta

Office staffs

Beta

Difference

in Betas

P-Value for

Difference z-score

PROQ → CS. 0.008 0.119*** 0.127 NaN -1.768*

403

Appendix 7.3- Comparison across groups for factors related to customer perceived value

Supermarket business models


BigC Beta

Lotte Mart

Beta

Difference

in Betas

P-Value for


SQ → CPV. 0.062† 0.209** -0.147 0.069 The positive relationship between CPV and SQ is stronger for Lotte Mart.

PROE → CPV. 0.153*** 0.024 0.129 0.028 The positive relationship between CPV and PROE is stronger for Coopmart or BigC.


BigC Beta

Vinmart

Beta

Difference

in Betas

P-Value for


PRICE → CPV. 0.263*** 0.365*** -0.102 0.015 The positive relationship between CPV and PRICE is stronger for Vinmart.


Beta

Vinmart

Beta

Difference

in Betas

P-Value for


SQ → CPV. 0.209** -0.032 0.241 0.014 The positive relationship between CPV and SQ is stronger for Lotte Mart.

CUSER → CPV. -0.008 0.119** -0.128 0.031 The positive relationship between CPV and CUSER is stronger for Vinmart.


BigC Beta Aeon Beta

Difference

in Betas

P-Value for


TRUST → CPV. 0.130*** 0.278*** -0.148 0.063 The positive relationship between CPV and TRUST is stronger for Aeon.

INCOME

Path Name

Under 5

million VND

Beta

From 5-10

million

VND Beta

Difference

in Betas

P-Value for


SQ → CPV. 0.006 0.156** -0.15 0.016 The positive relationship between CPV and SQ is stronger for From 5-10 million VND.

CUSER → CPV. 0.035 0.106*** -0.072 0.086 The positive relationship between CPV and CUSER is stronger for From 5-10 million

VND.

PRICE → CPV. 0.351*** 0.189*** 0.162 0.000 The positive relationship between CPV and PRICE is stronger for Under 5 million VND.

LOCATION

Path Name HCM Beta Hanoi Beta Difference

in Betas

P-Value for


PRICE → CPV. 0.213*** 0.377*** -0.164 0.002 The positive relationship between CPV and PRICE is stronger for Hanoi.

Path Name HCM Beta Da Nang

Beta

Difference

in Betas

P-Value for


PRICE → CPV. 0.213*** 0.363*** -0.15 0.027 The positive relationship between CPV and PRICE is stronger for Da Nang.

AGE RANGES


in Betas

P-Value for


CUSER → CPV. 0.027 0.113** -0.086 0.074 The positive relationship between CPV and CUSER is stronger for 23-30.

PRICE → CPV. 0.360*** 0.189*** 0.171 0.002 The positive relationship between CPV and PRICE is stronger for 18-22.

PROE → CPV. 0.082** 0.196*** -0.114 0.037 The positive relationship between CPV and PROE is stronger for 23-30.

TRUST → CPV. 0.206*** 0.104* 0.103 0.080 The positive relationship between CPV and TRUST is stronger for 18-22.

SQ → CPV. 0.000 0.180** -0.179 0.013 The positive relationship between CPV and SQ is stronger for 23-30.

Path Name 23-30 Beta above 55

Beta

Difference

in Betas

P-Value for


SQ → CPV. 0.180** -0.008 0.188 0.046 The positive relationship between CPV and SQ is stronger for 23-30.


in Betas

P-Value for


TRUST → CPV. 0.206*** 0.061 0.145 0.070 The positive relationship between CPV and TRUST is stronger for 18-22.

404

SQ → CPV. 0.000 0.198* -0.198 0.041 The positive relationship between CPV and SQ is stronger for 41-55.


in Betas

P-Value for


SWC → CPV. -0.015 -0.123*** 0.107 0.046 The negative relationship between CPV and SWC is stronger for 23-30.

GENDER

Path Name MALE Beta FEMALE

Beta

Difference

in Betas

P-Value for


PRICE → CPV. 0.220*** 0.326*** -0.105 0.039 The positive relationship between CPV and PRICE is stronger for FEMALE.

EDUCATION LEVEL

Path Name A levels Beta

College+ U

Beta

Difference

in Betas

P-Value for


TRUST → CPV. 0.172*** 0.343*** -0.171 0.056 The positive relationship between CPV and TRUST is stronger for College+ U.

OCCUPATION

Path Name

Housewife

Beta

Office staffs

Beta

Difference

in Betas

P-Value for


PRICE → CPV. 0.312*** 0.200*** 0.112 0.04 The positive relationship between CPV and PRICE is stronger for Housewife.

SQ → CPV. 0.026 0.153** -0.127 0.095 The positive relationship between CPV and SQ is stronger for Office staffs.

THE UNIVERSITY OF HULL Factors affecting customer loyalty ...

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